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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 20, Iss. 2 — Jan. 16, 2012
  • pp: 1151–1163
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Experimental validation of Mueller matrix differential decomposition

Noé Ortega-Quijano, Bicher Haj-Ibrahim, Enric García-Caurel, José Luis Arce-Diego, and Razvigor Ossikovski  »View Author Affiliations


Optics Express, Vol. 20, Issue 2, pp. 1151-1163 (2012)
http://dx.doi.org/10.1364/OE.20.001151


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Abstract

Mueller matrix differential decomposition is a novel method for retrieving the polarimetric properties of general depolarizing anisotropic media [N. Ortega-Quijano and J. L. Arce-Diego, Opt. Lett. 36, 1942 (2011), R. Ossikovski, Opt. Lett. 36, 2330 (2011)]. The method has been verified for Mueller matrices available in the literature. We experimentally validate the decomposition for five different experimental setups with different commutation properties and controlled optical parameters, comparing the differential decomposition with the forward and reverse polar decompositions. The results enable to verify the method and to highlight its advantages for certain experimental applications of high interest.

© 2012 OSA

1. Introduction

During the past decades Mueller matrix polarimetry has been established as the main technique for optically characterizing polarization elements and media [1

1. D. Goldstein, Polarized Light (Marcel Dekker, 2003).

]. As a consequence of the growing interest in the applications of polarimetric characterization techniques, the analysis of experimental data is becoming increasingly relevant. Specifically, Mueller matrix decomposition techniques play a key role for appropriately studying and interpreting measurements.

A considerable number of Mueller matrix decompositions have been proposed so far [2

2. R. Ossikovski, M. Anastasiadou, S. Ben Hatit, E. Garcia-Caurel, and A. De Martino, “Depolarizing Mueller matrices: how to decompose them,” Phys. Status Solidi (A) 205(4), 720–727 (2008). [CrossRef]

]. Cloude decomposition is a sum-based decomposition that enables to describe the predominant polarizing optical behavior of a certain sample, as well as characterizing its depolarizing properties [3

3. S. R. Cloude, “Group theory and polarisation algebra,” Optik (Stuttg.) 75, 26–36 (1986).

,4

4. S. R. Cloude, “Conditions for the physical realisability of matrix operators in polarimetry,” Proc. SPIE 1166, 177–185 (1989).

]. However, it is not able to separate all the optical effects and quantify them. Lu-Chipman polar decomposition [5

5. S. Y. Lu and R. A. Chipman, “Interpretation of Mueller matrices based on polar decomposition,” J. Opt. Soc. Am. A 13(5), 1106–1113 (1996). [CrossRef]

] was proposed as the generalization of the polar decomposition for depolarizing media [6

6. J. J. Gil and E. Bernabeu, “Obtainment of the polarizing and retardation parameters of a non-depolarizing optical system from the polar decomposition of its Mueller matrix,” Optik (Stuttg.) 76, 67–71 (1987).

], and after that the method was extended for all the possible orderings of the basic optical elements [7

7. J. Morio and F. Goudail, “Influence of the order of diattenuator, retarder, and polarizer in polar decomposition of Mueller matrices,” Opt. Lett. 29(19), 2234–2236 (2004). [CrossRef] [PubMed]

9

9. M. Anastasiadou, S. Ben Hatit, R. Ossikovski, S. Guyot, and A. De Martino, “Experimental validation of the reverse polar decomposition of depolarizing Mueller matrices,” J. Eur. Opt. Soc. Rapid Publ. 2, 070181–070187 (2007).

]. It is currently the most widely used method among experimentalists for analyzing Mueller matrices, and it has enabled to obtain fruitful results in many applications. Other remarkable decompositions are the normal form decomposition [10

10. R. Sridhar and R. Simon, “Normal form for Mueller matrices in polarization optics,” J. Mod. Opt. 41(10), 1903–1915 (1994). [CrossRef]

] and the symmetric decomposition [11

11. R. Ossikovski, “Analysis of depolarizing Mueller matrices through a symmetric decomposition,” J. Opt. Soc. Am. A 26(5), 1109–1118 (2009). [CrossRef] [PubMed]

,12

12. C. Fallet, A. Pierangelo, R. Ossikovski, and A. De Martino, “Experimental validation of the symmetric decomposition of Mueller matrices,” Opt. Express 18(2), 831–842 (2010). [CrossRef] [PubMed]

], being the latter comparatively easier to obtain and to interpret.

Despite the significant number of decompositions, there are still some difficulties that usually arise when experimentally measuring and analyzing samples. First of all, the order in which the effects take place in the sample may not be known a priori, and therefore the results are subjected to entail some errors [9

9. M. Anastasiadou, S. Ben Hatit, R. Ossikovski, S. Guyot, and A. De Martino, “Experimental validation of the reverse polar decomposition of depolarizing Mueller matrices,” J. Eur. Opt. Soc. Rapid Publ. 2, 070181–070187 (2007).

]. And secondly, there are media in which the effects are produced in a distributed way, homogeneously, and not in a sequential fashion. In this case, product decompositions are prone to fail. It is not an obvious task to quantify and determine the experimental errors committed in this case for real situations.

Recently, a novel decomposition based on the differential formulation of the Mueller calculus has been presented [13

13. N. Ortega-Quijano, F. Fanjul-Vélez, I. Salas-García, and J. L. Arce-Diego, “Comparative study of optical activity in chiral biological media by polar decomposition and differential Mueller matrices analysis,” Proc. SPIE 7906, 790612 (2011). [CrossRef]

17

17. R. Ossikovski, “Differential matrix formalism for depolarizing anisotropic media,” Opt. Lett. 36(12), 2330–2332 (2011). [CrossRef] [PubMed]

]. The method was first proposed [14

14. N. Ortega-Quijano and J. L. Arce-Diego, “Mueller matrix differential decomposition,” Opt. Lett. 36(10), 1942–1944 (2011). [CrossRef] [PubMed]

] as a natural consequence of the obtainment by means of Group theory of the complete set of differential Mueller matrices for describing general depolarizing anisotropic media [15

15. N. Ortega-Quijano and J. L. Arce-Diego, “Depolarizing differential Mueller matrices,” Opt. Lett. 36(13), 2429–2431 (2011). [CrossRef] [PubMed]

]. Independently, the method was also proposed from the point of view of the physical interpretation of the optical properties statistics by using the Minkowski antisymmetric and symmetric components [17

17. R. Ossikovski, “Differential matrix formalism for depolarizing anisotropic media,” Opt. Lett. 36(12), 2330–2332 (2011). [CrossRef] [PubMed]

]. In both cases, the differential Mueller calculus firstly proposed more than 30 years ago for non-depolarizing media [18

18. R. M. A. Azzam, “Propagation of partially polarized light through anisotropic media with or without depolarization: A differential 4x4 matrix calculus,” J. Opt. Soc. Am. 68(12), 1756–1767 (1978). [CrossRef]

] was extended for the general depolarizing case. Among the main advantages of the differential decomposition, the fact that it is specially suited for analyzing media with simultaneously occurring effects should be highlighted.

Mueller matrix differential decomposition has been proposed for both the forward and the backward direction. However, it has only been verified for a number of Mueller matrices of interest that can be found in the Optics literature. The aim of this work is to experimentally verify the method for several samples with controlled optical parameters and different characteristics in terms of number and ordering of optical effects.

2. Experimental

2.1 Polarimetric setup

The Mueller imaging polarimeter used in this work is schematically depicted in Fig. 1
Fig. 1 Optical scheme of the microscopic Mueller imaging polarimeter in transmission.
. The system can be divided into five main blocks: illumination system, polarization state generator, microscope system, polarization state analyzer, and detection system.

The illumination system is formed by a halogen lamp (Olympus CLH-SC, 150W) with the output fiber bundle at the focus of an aspherical condenser (Thorlabs AC254, f = 30 mm), followed by a cold mirror, an achromatic lens (Thorlabs AC254, f = 45 mm), a diffuser and an achromatic collimator (Thorlabs AC254, f = 80 mm). This combination is telecentric in both the object and the image space. The system provides a total homogeneous illumination spot of about 2 cm diameter, which can be reduced by using a diaphragm. A beam splitter enables to take a reference in order to perform source normalization.

After the illumination system, an achromatic lens (Thorlabs AC254, f = 50 mm) focuses the incident light on the polarization state generator (PSG), which is composed of a linear polarizer (Melles Griot, 03 FPG 007) and two nematic liquid crystals variable retarders (Meadowlark LVR 300). At the output, an achromatic lens (Thorlabs AC254, f = 60 mm) collimates the spot. The design of the PSG design was performed following the optimized method developed in [19

19. B. Laude-Boulesteix, A. De Martino, B. Drévillon, and L. Schwartz, “Mueller polarimetric imaging system with liquid crystals,” Appl. Opt. 43(14), 2824–2832 (2004). [CrossRef] [PubMed]

].

The microscope system is formed by the usual combination of condenser and objective. The objective used is a plan achromatic microscopic objective lens (Olympus SLMPlan 20x) with a numerical aperture of 0.35.

The polarization state analyzer (PSA) is similar to the PSG, with a reverse disposition of the optical components, and following the same optimized design.

An ensemble formed by an achromatic lens (Thorlabs AC254, f = 100 mm) followed by a mirror and a second lens (Thorlabs AC254, f = 200 mm) projects the light spot in the detection system. Imaging is performed by a CCD camera (AVT Stingray F-080C, 786x432 pixels, 14 bits) with the aid of a zoom (Pentax TV lens 50 mm). An interference filter with a spectral bandwidth of 20 nm is placed before the detector in order to fix the detection wavelength, which in this case is fixed to 550 nm. The value of the dark current of the camera is taken before each measurement and is subtracted from the signal for each pixel. Five acquisitions were averaged for each measure in order to optimize the signal-to-noise ratio and subsequently increase the robustness and repeatability of the measurement. The calibration was performed using the Eigenvalue Calibration Method [20

20. E. Compain, S. Poirier, and B. Drevillon, “General and self-consistent method for the calibration of polarization modulators, polarimeters, and mueller-matrix ellipsometers,” Appl. Opt. 38(16), 3490–3502 (1999). [CrossRef] [PubMed]

].

2.2 Samples

We have measured five different types of samples with different combinations of commutative and non-commutative optical effects that occur in a sequential and/or distributed way. They are shown in Fig. 2
Fig. 2 Experimental samples scheme corresponding to a cuvette filled with a) glucose and milk dilution in distilled water, and milk dilution in distilled water with b) a linear polarizer at the bottom, c) a linear polarizer at the top, d) a linear polarizer symmetrically fixed inside the container, and e) a linear polarizer asymmetrically fixed inside the container. Dimensions are given in the text. The small arrow on the left indicates the light propagation direction.
, where the arrow indicates the direction of light propagation.

2.2.1 Glucose and milk dilution in distilled water

The first sample (Fig. 2a) is an optically active turbid medium. A milk dilution in distilled water with different volume fractions was chosen as lipid-based scattering medium. Scattering in milk is produced fat globules surrounded by a lipid bilayer, which are typically 1 to 2 µm diameter, and also by casein proteins of about 0.15 µm diameter [21

21. M. D. Waterworth, B. J. Tarte, A. J. Joblin, T. van Doorn, and H. E. Niesler, “Optical transmission properties of homogenised milk used as a phantom material in visible wavelength imaging,” Australas. Phys. Eng. Sci. Med. 18(1), 39–44 (1995). [PubMed]

]. We used homogenized pasteurized milk with a fat content of 1.55%. The general form of the normalized Mueller matrix for such turbid medium is a diagonal depolarizer
Mturbid=[10000dl0000dl0000dc],
(1)
which is in agreement with the Mueller matrix observed in media with randomly located nearly spherical particles [22

22. M. I. Mishchenko, J. W. Hovenier, and L. D. Travis, Light Scattering by Nonspherical Particles (Academic, 2000).

]. The dl and dc coefficients that characterize the diagonal depolarization shown by this kind of sample obviously vary according to the experimental parameters that determine the ensemble-averaged Mueller matrix measured in each case. Dextrogyre optical activity is obtained by adding different concentrations of glucose to the solution. The Mueller matrix for optical activity Moa is a rotation matrix. As long as the linear depolarization of the turbid medium is orientation-independent for linearly polarized light, the Mueller matrices of depolarization and optical activity remarkably commute:
MoaMturbid=MturbidMoa=[10000dlcos2θdlsin2θ00dlsin2θdlcos2θ0000dc],
(2)
where θ is the rotation angle. The optical rotatory power of glucose at 550 nm is 61.36 °/(dm·g/mL) [23

23. R. R. Ansari, S. Böckle, and L. Rovati, “New optical scheme for a polarimetric-based glucose sensor,” J. Biomed. Opt. 9(1), 103–115 (2004). [CrossRef] [PubMed]

]. The solution was placed in a transparent glass cuvette with transversal dimensions of about 30x30 mm and a sample length of 10 mm.

2.2.2 Milk dilution with a linear polarizer at the bottom or at the top

The second and third samples are a combination a linear diattenuator and the turbid medium composed of milk and distilled water described above, which are placed sequentially with the diattenuator before (Fig. 2b) or after (Fig. 2c) the depolarizing medium. The diattenuator used in this work is a Polaroid film which was fixed into the cuvette with the transmission axis aligned with the horizontal axis of the detector. The length of the depolarizing medium in this case is 6.5 mm.

The Mueller matrices of depolarization and linear diattenuation do not commute. The Mueller matrix for the diattenuator followed by the depolarizer is
MturbidMd(p)=[1p00dlpdl0000dl(1p2)1/20000dc(1p2)1/2],
(4)
while the matrix for the reverse order (depolarizer followed by the diattenuator) is
Md(p)Mturbid=[1dlp00pdl0000dl(1p2)1/20000dc(1p2)1/2].
(5)
So, in fact, it is readily verified that the Mueller matrix corresponding to one of the possible ordering of the elements is just the transpose of the other one. This fact is relevant for the assessment of the experimental data presented in Section 3.

2.2.3 Milk dilution with a linear polarizer inside the container

The last two samples are similar to the second and third samples, with the relevant difference that the polarizer is placed inside the turbid medium. The Mueller matrix in this case is:

Mturbid2Md(p)Mturbid1=[1dl1p00dl2pdl1dl20000dl1dl2(1p2)1/20000dc1dc2(1p2)1/2].
(6)

In the fourth sample (Fig. 2d) the linear polarizer is symmetrically fixed inside the container (which in this case has a total length of 13 mm) so it can be considered that dl1=dl2=dl. When macroscopically measured, such type of sample constitutes an appropriate model of a medium with distributed simultaneous optical properties. The last sample (Fig. 2e) has the linear polarizer asymmetrically fixed inside a glass container of 10 mm, with a distance of 3.5 mm to the bottom and 6.5 mm to the top, so for this situation dl1dl2.

2.3 Method

The microscopic Mueller imaging polarimeter described above gives sixteen images corresponding to each Mueller matrix coefficient. Each image is 800x600 pixels, from which the active area radius is 350 pixels. For this study we select a fixed 40x40 pixels window in the center of the image. All the images are normalized to the first Mueller matrix element.

The first step is filtering the measured matrix in order to correct residual experimental errors and ensure that the physical realizability condition of the measured Mueller matrix is fulfilled [4

4. S. R. Cloude, “Conditions for the physical realisability of matrix operators in polarimetry,” Proc. SPIE 1166, 177–185 (1989).

]. The filtering procedure requires calculating the covariance matrix C from the Mueller matrix M for each pixel
C=i,j=14Mij(σiσj*),
(7)
where * denotes the complex conjugate and is the Kronecker product that enables to obtain the sixteen Dirac matrices from the Pauli spin matrices σi. The covariance matrix is further diagonalized by a conventional eigen decomposition so that C=VCDCVC-1, where DC is a diagonal matrix with the eigenvalues of C (we will denote them λC) and VC contains its eigenvectors column-wise. Matrix filtering consists on fixing any negative eigenvalue to zero, and subsequently obtaining the filtered Mueller matrix by inverting Eq. (7).

Once the matrix has been filtered, it is decomposed by two different methods: the polar decomposition [5

5. S. Y. Lu and R. A. Chipman, “Interpretation of Mueller matrices based on polar decomposition,” J. Opt. Soc. Am. A 13(5), 1106–1113 (1996). [CrossRef]

7

7. J. Morio and F. Goudail, “Influence of the order of diattenuator, retarder, and polarizer in polar decomposition of Mueller matrices,” Opt. Lett. 29(19), 2234–2236 (2004). [CrossRef] [PubMed]

] and the differential decomposition [14

14. N. Ortega-Quijano and J. L. Arce-Diego, “Mueller matrix differential decomposition,” Opt. Lett. 36(10), 1942–1944 (2011). [CrossRef] [PubMed]

17

17. R. Ossikovski, “Differential matrix formalism for depolarizing anisotropic media,” Opt. Lett. 36(12), 2330–2332 (2011). [CrossRef] [PubMed]

]. Regarding polar decomposition, we will use two specific decompositions out of the six possible products, namely the forward decomposition in its most common order
M=MΔfMRfMDf,
(8)
which is usually called Lu-Chipman polar decomposition with reference to the authors that first proposed it, and the reverse decomposition in its form

M=MRrMDrMΔr.
(9)

The differential decomposition is performed by obtaining the accumulated differential Mueller matrix from the matrix logarithm of the macroscopic Mueller matrix
m¯=logm(M),
(10)
which can be easily calculated by the eigen analysis of M, and further decomposing it into the 16 differential parameters that characterize general depolarizing anisotropic media [14

14. N. Ortega-Quijano and J. L. Arce-Diego, “Mueller matrix differential decomposition,” Opt. Lett. 36(10), 1942–1944 (2011). [CrossRef] [PubMed]

,17

17. R. Ossikovski, “Differential matrix formalism for depolarizing anisotropic media,” Opt. Lett. 36(12), 2330–2332 (2011). [CrossRef] [PubMed]

].

In this work we have used three different parameters to characterize the optical properties of the measured samples: optical rotation, diattenuation coefficient, and entropy. These parameters are calculated for each pixel, and the results are statistically analyzed to obtain the mean value and the standard deviation in the observation window. Optical rotation can be calculated from the retardance component of any polar decomposition as
Ψlc=12atan[MR(3,2)MR(2,3)MR(2,2)+MR(3,3)],
(11)
while for differential decomposition the optical rotation is simply given by
Ψdd=η¯v/2,
(12)
where the minus sign arises from the sign convention adopted in the definition of the general differential Mueller matrix. Regarding the diattenuation coefficient, it can be obtained from the diattenuation component of polar decomposition

Dlc=1MD(1,1)[MD(1,2)2+MD(1,3)2+MD(1,4)2]1/2.
(13)

In the case of differential decomposition, the diattenuation coefficient is given as a function of the elementary optical properties of the sample by
Ddd=tanh[(κ¯q2+κ¯u2+κ¯v2)1/2],
(14)
where κ¯q, κ¯u and κ¯vare the accumulated differential parameters for linear x-y, linear ± 45° and circular dichroism, respectively [14

14. N. Ortega-Quijano and J. L. Arce-Diego, “Mueller matrix differential decomposition,” Opt. Lett. 36(10), 1942–1944 (2011). [CrossRef] [PubMed]

]. It should be highlighted that the accumulated differential parameters diverge for an ideal depolarizer, while the diattenuation coefficient defined in Eq. (14) always takes values below 1, as expected from the definition of this metric. This expression for calculating the diattenuation coefficient can be easily obtained from the solution of the differential matrix and Mueller matrix eigenvalue equations [18

18. R. M. A. Azzam, “Propagation of partially polarized light through anisotropic media with or without depolarization: A differential 4x4 matrix calculus,” J. Opt. Soc. Am. 68(12), 1756–1767 (1978). [CrossRef]

] in a similar way as it was performed for the differential Jones matrix of a general diattenuator [5

5. S. Y. Lu and R. A. Chipman, “Interpretation of Mueller matrices based on polar decomposition,” J. Opt. Soc. Am. A 13(5), 1106–1113 (1996). [CrossRef]

].

Finally, depolarization is quantified by the entropy-like depolarization metric H [3

3. S. R. Cloude, “Group theory and polarisation algebra,” Optik (Stuttg.) 75, 26–36 (1986).

], defined from the eigenvalues of the Cloude coherency matrix as

H=i=14xilog4xi,xi=λCi/j=14λCi.
(15)

3. Results

3.1 Validation for commutative distributed effects

The first set of measurements was performed on optically active turbid samples as already described in Section 2.2. Glucose concentrations of 0M, 0.62M, 1.15M, 1.62M and 2.03M were measured with several milk concentrations for each of them, in order to have entropy values from 0 (no depolarization) to nearly 1 (complete depolarization). First of all, the scattering solution without glucose was measured for control purposes. Figure 3
Fig. 3 Optical rotation as a function of the scatterer concentration for a milk dilution in distilled water without glucose. The theoretical value (zero) is depicted as a reference. The inset at the bottom shows the Cloude entropy for each value of milk volume fraction. Error bars represent the standard deviation, which overlaps for the three decompositions.
shows the mean values and standard deviations obtained for the 40x40 pixels window as described in Section 2.3. The calculated optical rotation is nearly zero for all cases. The standard deviation of the measurement (which coincides for the three decompositions) increases as depolarization becomes stronger, but the stability of the average optical rotation values confirms the quality of the measurements. It can be observed that the results all the decompositions overlap, as expected for commutative optical effects, as long as the order assumption performed in polar decomposition does not affect in this case.

The results for glucose concentrations of 1.15M are presented in Fig. 4
Fig. 4 Optical rotation as a function of the scatterer concentration for a milk dilution in distilled water with a glucose molar concentration of 1.15M. The theoretical value (zero) is depicted as a reference. The inset at the bottom shows the Cloude entropy for each value of milk volume fraction. Error bars represent the standard deviation, which overlaps for the three decompositions.
(similar results were obtained for the rest of concentrations and are not shown here for the sake of conciseness). The calculated optical rotation for the cuvette length is 1.47 degrees (it has been depicted with a grey line). The experimental results are in very good agreement with the expected value. A remarkable increase in the standard deviation is observed in the same way as above. It is interesting to note that the observed optical rotation slightly increases for higher milk concentrations. This effect is due to the average path length increase caused by multiple scattering, and has already been observed in other experimental measurements [24

24. S. Manhas, M. K. Swami, P. Buddhiwant, N. Ghosh, P. K. Gupta, and J. Singh, “Mueller matrix approach for determination of optical rotation in chiral turbid media in backscattering geometry,” Opt. Express 14(1), 190–202 (2006). [CrossRef] [PubMed]

]. The results obtained by the three decompositions coincide again, which enables to validate the experimental accuracy of Mueller matrix differential decomposition.

3.2 Comparison for non-commutative sequential effects

The results obtained by polar decomposition depend on the choice of the most appropriate sub-type of decomposition for a certain measurement. The accuracy of the results is obviously better if the assumption about the order in which the optical effects take place corresponds to the real physical conditions of the experiment. However, the choice becomes difficult if no aprioristic information about the sample is known. In this case, the non-commutativity of matrix products can lead to erroneous results [7

7. J. Morio and F. Goudail, “Influence of the order of diattenuator, retarder, and polarizer in polar decomposition of Mueller matrices,” Opt. Lett. 29(19), 2234–2236 (2004). [CrossRef] [PubMed]

9

9. M. Anastasiadou, S. Ben Hatit, R. Ossikovski, S. Guyot, and A. De Martino, “Experimental validation of the reverse polar decomposition of depolarizing Mueller matrices,” J. Eur. Opt. Soc. Rapid Publ. 2, 070181–070187 (2007).

].

Several measurements have been performed on samples with sequential effects in order to observe the order-dependence of polar decomposition and compare it with the results obtained by the differential decomposition for such kind of samples. The first sample is a diattenuator followed by a depolarizer (Fig. 2b). The measured diattenuation coefficient for the Polaroid film alone is 0.9992. Figure 6
Fig. 6 Diattenuation coefficient as a function of the milk volume fraction for the configuration diattenuator-depolarizer (Fig. 2b). The inset at the bottom shows the Cloude entropy for each value of milk volume fraction.
shows the diattenuation coefficient obtained for several milk volume fractions, as well as the Cloude entropy of each sample. The diattenuation coefficient calculated by the differential decomposition and the forward polar decomposition is roughly one for all cases, as expected. However, it can be observed that the reverse polar decomposition is assuming the wrong order, which provokes a stronger error in the results for increasing depolarization. We should recall that the forward and reverse polar decompositions obviously give the same result when the entropy is small (in that situation there is only an optical effect, as long as no depolarization is produced in the sample).

3.3 Comparison for non-commutative distributed-like effects

Apart from the choice of the order, there is another problem that usually arises: there are many samples in which the optical effects take place simultaneously, in a distributed way. Biological tissues constitute a relevant example of such kind of media. In that case, the assumption of sequential and discrete optical effects is arbitrary and does not correspond to the real physical characteristics of the sample. Even if the errors can remain moderate for certain conditions [28

28. N. Ghosh, M. F. G. Wood, and I. A. Vitkin, “Influence of the order of the constituent basis matrices on the Mueller matrix decomposition-derived polarization parameters in complex turbid media such as biological tissues,” Opt. Commun. 283(6), 1200–1208 (2010). [CrossRef]

], using a family of decompositions that are based on non-commutative matrix products constitutes a not so suitable methodology. For such kind of experimental samples, the differential Mueller matrix decomposition constitutes a more appropriate approach, as long as it is order-independent and it appropriately models simultaneous optical effects at the microscopic level.

In order to verify the differential decomposition for such kind of media, we have measured the milk dilution with the polarizer in the middle (Fig. 2d) described in Section 2.2, as long as it mimics a medium with non-commutative distributed effects. The fact that this sample has controlled optical properties is determinant for the verification of our method, as a necessary step before applying it for analyzing media of increasing complexity.

For this sample, both the forward and reverse polar decompositions give erroneous results for the diattenuation coefficient. From Eq. (6) it can be easily seen that a diattenuation coefficient of dlp is obtained by both polar decompositions when the Polaroid is symmetrically placed inside the container. The experimental results are shown in Fig. 8
Fig. 8 Diattenuation coefficient as a function of the milk volume fraction for the polarizer symmetrically placed inside the turbid medium (Fig. 2d).
. Effectively, it can be observed that the diattenuation coefficient calculated by polar decomposition begins to fail as soon as the depolarization shown by the sample becomes noticeable. The values calculated by the forward and reverse decompositions are roughly the same, as predicted (the slight difference between them is likely due to small differences in the turbid medium length before and after the polarizer). However, the differential decomposition shows a robust behavior in the determination of the diattenuation coefficient for all cases. In effect, it manages to decouple the optical effects and successfully characterizes the diattenuation properties of the sample.

4. Conclusions

The experimental verification of Mueller matrix differential decomposition has been presented for the first time. The validation of this method has been demonstrated for several types of media measured in transmission. Samples with commutative distributed effects, non-commutative sequential effects, and non-commutative distributed-like ones have been measured and analyzed using the forward and reverse polar decompositions and the differential decomposition. The results enable to assess the validity of the differential decomposition for appropriately analyzing the experimental data obtained by imaging Mueller polarimeters. The order-independence of the differential decomposition and its suitability for studying media with simultaneous optical effects makes it a technique with a high potential for many applications. In particular, the analysis of biological tissues polarimetric images seems one of the most interesting applications of this novel method.

Acknowledgments

This work has been partially funded by the San Cándido Foundation, Santander (Spain). Part of this work has been supported by a Predoctoral Grant of the University of Cantabria. Bicher Haj-Ibrahim gratefully recognizes partial funding within the ANR ScatteroMueller contract.

References and links

1.

D. Goldstein, Polarized Light (Marcel Dekker, 2003).

2.

R. Ossikovski, M. Anastasiadou, S. Ben Hatit, E. Garcia-Caurel, and A. De Martino, “Depolarizing Mueller matrices: how to decompose them,” Phys. Status Solidi (A) 205(4), 720–727 (2008). [CrossRef]

3.

S. R. Cloude, “Group theory and polarisation algebra,” Optik (Stuttg.) 75, 26–36 (1986).

4.

S. R. Cloude, “Conditions for the physical realisability of matrix operators in polarimetry,” Proc. SPIE 1166, 177–185 (1989).

5.

S. Y. Lu and R. A. Chipman, “Interpretation of Mueller matrices based on polar decomposition,” J. Opt. Soc. Am. A 13(5), 1106–1113 (1996). [CrossRef]

6.

J. J. Gil and E. Bernabeu, “Obtainment of the polarizing and retardation parameters of a non-depolarizing optical system from the polar decomposition of its Mueller matrix,” Optik (Stuttg.) 76, 67–71 (1987).

7.

J. Morio and F. Goudail, “Influence of the order of diattenuator, retarder, and polarizer in polar decomposition of Mueller matrices,” Opt. Lett. 29(19), 2234–2236 (2004). [CrossRef] [PubMed]

8.

R. Ossikovski, A. De Martino, and S. Guyot, “Forward and reverse product decompositions of depolarizing Mueller matrices,” Opt. Lett. 32(6), 689–691 (2007). [CrossRef] [PubMed]

9.

M. Anastasiadou, S. Ben Hatit, R. Ossikovski, S. Guyot, and A. De Martino, “Experimental validation of the reverse polar decomposition of depolarizing Mueller matrices,” J. Eur. Opt. Soc. Rapid Publ. 2, 070181–070187 (2007).

10.

R. Sridhar and R. Simon, “Normal form for Mueller matrices in polarization optics,” J. Mod. Opt. 41(10), 1903–1915 (1994). [CrossRef]

11.

R. Ossikovski, “Analysis of depolarizing Mueller matrices through a symmetric decomposition,” J. Opt. Soc. Am. A 26(5), 1109–1118 (2009). [CrossRef] [PubMed]

12.

C. Fallet, A. Pierangelo, R. Ossikovski, and A. De Martino, “Experimental validation of the symmetric decomposition of Mueller matrices,” Opt. Express 18(2), 831–842 (2010). [CrossRef] [PubMed]

13.

N. Ortega-Quijano, F. Fanjul-Vélez, I. Salas-García, and J. L. Arce-Diego, “Comparative study of optical activity in chiral biological media by polar decomposition and differential Mueller matrices analysis,” Proc. SPIE 7906, 790612 (2011). [CrossRef]

14.

N. Ortega-Quijano and J. L. Arce-Diego, “Mueller matrix differential decomposition,” Opt. Lett. 36(10), 1942–1944 (2011). [CrossRef] [PubMed]

15.

N. Ortega-Quijano and J. L. Arce-Diego, “Depolarizing differential Mueller matrices,” Opt. Lett. 36(13), 2429–2431 (2011). [CrossRef] [PubMed]

16.

N. Ortega-Quijano and J. L. Arce-Diego, “Mueller matrix differential decomposition for direction reversal: application to samples measured in reflection and backscattering,” Opt. Express 19(15), 14348–14353 (2011). [CrossRef] [PubMed]

17.

R. Ossikovski, “Differential matrix formalism for depolarizing anisotropic media,” Opt. Lett. 36(12), 2330–2332 (2011). [CrossRef] [PubMed]

18.

R. M. A. Azzam, “Propagation of partially polarized light through anisotropic media with or without depolarization: A differential 4x4 matrix calculus,” J. Opt. Soc. Am. 68(12), 1756–1767 (1978). [CrossRef]

19.

B. Laude-Boulesteix, A. De Martino, B. Drévillon, and L. Schwartz, “Mueller polarimetric imaging system with liquid crystals,” Appl. Opt. 43(14), 2824–2832 (2004). [CrossRef] [PubMed]

20.

E. Compain, S. Poirier, and B. Drevillon, “General and self-consistent method for the calibration of polarization modulators, polarimeters, and mueller-matrix ellipsometers,” Appl. Opt. 38(16), 3490–3502 (1999). [CrossRef] [PubMed]

21.

M. D. Waterworth, B. J. Tarte, A. J. Joblin, T. van Doorn, and H. E. Niesler, “Optical transmission properties of homogenised milk used as a phantom material in visible wavelength imaging,” Australas. Phys. Eng. Sci. Med. 18(1), 39–44 (1995). [PubMed]

22.

M. I. Mishchenko, J. W. Hovenier, and L. D. Travis, Light Scattering by Nonspherical Particles (Academic, 2000).

23.

R. R. Ansari, S. Böckle, and L. Rovati, “New optical scheme for a polarimetric-based glucose sensor,” J. Biomed. Opt. 9(1), 103–115 (2004). [CrossRef] [PubMed]

24.

S. Manhas, M. K. Swami, P. Buddhiwant, N. Ghosh, P. K. Gupta, and J. Singh, “Mueller matrix approach for determination of optical rotation in chiral turbid media in backscattering geometry,” Opt. Express 14(1), 190–202 (2006). [CrossRef] [PubMed]

25.

J. S. Maier, S. A. Walker, S. Fantini, M. A. Franceschini, and E. Gratton, “Possible correlation between blood glucose concentration and the reduced scattering coefficient of tissues in the near infrared,” Opt. Lett. 19(24), 2062–2064 (1994). [CrossRef] [PubMed]

26.

J. T. Bruulsema, J. E. Hayward, T. J. Farrell, M. S. Patterson, L. Heinemann, M. Berger, T. Koschinsky, J. Sandahl-Christiansen, H. Orskov, M. Essenpreis, G. Schmelzeisen-Redeker, and D. Böcker, “Correlation between blood glucose concentration in diabetics and noninvasively measured tissue optical scattering coefficient,” Opt. Lett. 22(3), 190–192 (1997). [CrossRef] [PubMed]

27.

A. N. Bashkatov, E. A. Genina, Y. P. Sinichkin, N. A. Lakodina, V. I. Kochubey, and V. V. Tuchin, “Estimation of glucose diffusion coefficient in scleral tissue,” Proc. SPIE 4001, 345–355 (2000). [CrossRef]

28.

N. Ghosh, M. F. G. Wood, and I. A. Vitkin, “Influence of the order of the constituent basis matrices on the Mueller matrix decomposition-derived polarization parameters in complex turbid media such as biological tissues,” Opt. Commun. 283(6), 1200–1208 (2010). [CrossRef]

OCIS Codes
(120.5410) Instrumentation, measurement, and metrology : Polarimetry
(260.2130) Physical optics : Ellipsometry and polarimetry
(260.5430) Physical optics : Polarization

ToC Category:
Instrumentation, Measurement, and Metrology

History
Original Manuscript: October 14, 2011
Manuscript Accepted: November 17, 2011
Published: January 4, 2012

Citation
Noé Ortega-Quijano, Bicher Haj-Ibrahim, Enric García-Caurel, José Luis Arce-Diego, and Razvigor Ossikovski, "Experimental validation of Mueller matrix differential decomposition," Opt. Express 20, 1151-1163 (2012)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-20-2-1151


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References

  1. D. Goldstein, Polarized Light (Marcel Dekker, 2003).
  2. R. Ossikovski, M. Anastasiadou, S. Ben Hatit, E. Garcia-Caurel, and A. De Martino, “Depolarizing Mueller matrices: how to decompose them,” Phys. Status Solidi (A)205(4), 720–727 (2008). [CrossRef]
  3. S. R. Cloude, “Group theory and polarisation algebra,” Optik (Stuttg.)75, 26–36 (1986).
  4. S. R. Cloude, “Conditions for the physical realisability of matrix operators in polarimetry,” Proc. SPIE1166, 177–185 (1989).
  5. S. Y. Lu and R. A. Chipman, “Interpretation of Mueller matrices based on polar decomposition,” J. Opt. Soc. Am. A13(5), 1106–1113 (1996). [CrossRef]
  6. J. J. Gil and E. Bernabeu, “Obtainment of the polarizing and retardation parameters of a non-depolarizing optical system from the polar decomposition of its Mueller matrix,” Optik (Stuttg.)76, 67–71 (1987).
  7. J. Morio and F. Goudail, “Influence of the order of diattenuator, retarder, and polarizer in polar decomposition of Mueller matrices,” Opt. Lett.29(19), 2234–2236 (2004). [CrossRef] [PubMed]
  8. R. Ossikovski, A. De Martino, and S. Guyot, “Forward and reverse product decompositions of depolarizing Mueller matrices,” Opt. Lett.32(6), 689–691 (2007). [CrossRef] [PubMed]
  9. M. Anastasiadou, S. Ben Hatit, R. Ossikovski, S. Guyot, and A. De Martino, “Experimental validation of the reverse polar decomposition of depolarizing Mueller matrices,” J. Eur. Opt. Soc. Rapid Publ.2, 070181–070187 (2007).
  10. R. Sridhar and R. Simon, “Normal form for Mueller matrices in polarization optics,” J. Mod. Opt.41(10), 1903–1915 (1994). [CrossRef]
  11. R. Ossikovski, “Analysis of depolarizing Mueller matrices through a symmetric decomposition,” J. Opt. Soc. Am. A26(5), 1109–1118 (2009). [CrossRef] [PubMed]
  12. C. Fallet, A. Pierangelo, R. Ossikovski, and A. De Martino, “Experimental validation of the symmetric decomposition of Mueller matrices,” Opt. Express18(2), 831–842 (2010). [CrossRef] [PubMed]
  13. N. Ortega-Quijano, F. Fanjul-Vélez, I. Salas-García, and J. L. Arce-Diego, “Comparative study of optical activity in chiral biological media by polar decomposition and differential Mueller matrices analysis,” Proc. SPIE7906, 790612 (2011). [CrossRef]
  14. N. Ortega-Quijano and J. L. Arce-Diego, “Mueller matrix differential decomposition,” Opt. Lett.36(10), 1942–1944 (2011). [CrossRef] [PubMed]
  15. N. Ortega-Quijano and J. L. Arce-Diego, “Depolarizing differential Mueller matrices,” Opt. Lett.36(13), 2429–2431 (2011). [CrossRef] [PubMed]
  16. N. Ortega-Quijano and J. L. Arce-Diego, “Mueller matrix differential decomposition for direction reversal: application to samples measured in reflection and backscattering,” Opt. Express19(15), 14348–14353 (2011). [CrossRef] [PubMed]
  17. R. Ossikovski, “Differential matrix formalism for depolarizing anisotropic media,” Opt. Lett.36(12), 2330–2332 (2011). [CrossRef] [PubMed]
  18. R. M. A. Azzam, “Propagation of partially polarized light through anisotropic media with or without depolarization: A differential 4x4 matrix calculus,” J. Opt. Soc. Am.68(12), 1756–1767 (1978). [CrossRef]
  19. B. Laude-Boulesteix, A. De Martino, B. Drévillon, and L. Schwartz, “Mueller polarimetric imaging system with liquid crystals,” Appl. Opt.43(14), 2824–2832 (2004). [CrossRef] [PubMed]
  20. E. Compain, S. Poirier, and B. Drevillon, “General and self-consistent method for the calibration of polarization modulators, polarimeters, and mueller-matrix ellipsometers,” Appl. Opt.38(16), 3490–3502 (1999). [CrossRef] [PubMed]
  21. M. D. Waterworth, B. J. Tarte, A. J. Joblin, T. van Doorn, and H. E. Niesler, “Optical transmission properties of homogenised milk used as a phantom material in visible wavelength imaging,” Australas. Phys. Eng. Sci. Med.18(1), 39–44 (1995). [PubMed]
  22. M. I. Mishchenko, J. W. Hovenier, and L. D. Travis, Light Scattering by Nonspherical Particles (Academic, 2000).
  23. R. R. Ansari, S. Böckle, and L. Rovati, “New optical scheme for a polarimetric-based glucose sensor,” J. Biomed. Opt.9(1), 103–115 (2004). [CrossRef] [PubMed]
  24. S. Manhas, M. K. Swami, P. Buddhiwant, N. Ghosh, P. K. Gupta, and J. Singh, “Mueller matrix approach for determination of optical rotation in chiral turbid media in backscattering geometry,” Opt. Express14(1), 190–202 (2006). [CrossRef] [PubMed]
  25. J. S. Maier, S. A. Walker, S. Fantini, M. A. Franceschini, and E. Gratton, “Possible correlation between blood glucose concentration and the reduced scattering coefficient of tissues in the near infrared,” Opt. Lett.19(24), 2062–2064 (1994). [CrossRef] [PubMed]
  26. J. T. Bruulsema, J. E. Hayward, T. J. Farrell, M. S. Patterson, L. Heinemann, M. Berger, T. Koschinsky, J. Sandahl-Christiansen, H. Orskov, M. Essenpreis, G. Schmelzeisen-Redeker, and D. Böcker, “Correlation between blood glucose concentration in diabetics and noninvasively measured tissue optical scattering coefficient,” Opt. Lett.22(3), 190–192 (1997). [CrossRef] [PubMed]
  27. A. N. Bashkatov, E. A. Genina, Y. P. Sinichkin, N. A. Lakodina, V. I. Kochubey, and V. V. Tuchin, “Estimation of glucose diffusion coefficient in scleral tissue,” Proc. SPIE4001, 345–355 (2000). [CrossRef]
  28. N. Ghosh, M. F. G. Wood, and I. A. Vitkin, “Influence of the order of the constituent basis matrices on the Mueller matrix decomposition-derived polarization parameters in complex turbid media such as biological tissues,” Opt. Commun.283(6), 1200–1208 (2010). [CrossRef]

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