1. Introduction
Wavefront coding [
1E. R. Dowski Jr and W. T. Cathey, “Extended depth of field through wave-front coding,” Appl. Opt. 34(11), 1859–1866 (1995). [CrossRef] [PubMed]
] is a hybrid optical-digital technology, consisting of optical encoding and digital decoding. Digital decoding, which makes up for the deficiencies introduced by optical design, leads to the increase of the degrees of freedom in optical design. Consequently, this technology provides new opportunities for optical instruments, which cannot be achieved based on traditional optics design methods.
The depth of field extending is one of classic examples based on wavefront coding. With a special phase mask added on the pupil, the system is insensitive to defocus. The defocus invariant PSF (point spread function) is used as the deconvolution kernel in digital decoding to obtain sharp images. It is apparent that choosing an optimal phase mask is a key process for the design of wavefront coding system. Although there are many kinds of phase masks [
1E. R. Dowski Jr and W. T. Cathey, “Extended depth of field through wave-front coding,” Appl. Opt. 34(11), 1859–1866 (1995). [CrossRef] [PubMed]
–
3H. Zhao and Y. Li, “Optimized logarithmic phase masks used to generate defocus invariant modulation transfer function for wavefront coding system,” Opt. Lett. 35(15), 2630–2632 (2010). [CrossRef] [PubMed]
], cubic phase mask is one of most widely used types.
Most analysis of wavefront coding has been carried out within the systems with a rectangular pupil [
1E. R. Dowski Jr and W. T. Cathey, “Extended depth of field through wave-front coding,” Appl. Opt. 34(11), 1859–1866 (1995). [CrossRef] [PubMed]
,
4G. Muyo and A. R. Harvey, “Decomposition of the optical transfer function: wavefront coding imaging systems,” Opt. Lett. 30(20), 2715–2717 (2005). [CrossRef] [PubMed]
,
5] due to the simplicity of the analysis in either frequency or space domain. The rectangular pupil assumption allows the double integral involved in the analysis to be written as the product of two separate 1D integrals. However, most of pupils in optical systems are circular instead of rectangular. Thereby, those analysis results cannot accurately reflect the imaging characteristics of most wavefront coding systems. Bagheri et al [
6S. Bagheri, P. E. Silveira, and D. P. de Farias, “Analytical optimal solution of the extension of the depth of field using cubic-phase wavefront coding. part I. reduced-complexity approximate representation of the modulation transfer function,” J. Opt. Soc. Am. A 25(5), 1051–1063 (2008). [CrossRef] [PubMed]
] investigated the modulation transfer function (MTF) of the circular pupil system. However, they just focused on the axial properties of MTF and did not give the analysis of the entire frequency plane. In our previous paper [
5], the stationary phase method was proposed to analyze the PSF of the wavefront coding system with a rectangular pupil and the obtained results were agreed well with those obtained by Fast Fourier Transform approach. In this paper, the PSF analysis method is extended to the circular pupil in space domain. The approximated representation of the PSF in a circular pupil wavefront coding system is deducted based on the stationary phase method. The defocus influence on PSF and decoded images are discussed in detail. The similarities and differences of the PSFs between the rectangular and circular pupil systems are given.
2. Approximated PSF with a circular pupil
2.1 Defocused PSF
The defocused PSF
of an incoherent wavefront coding system can be written as
where
is the wavenumber;
is the square root of −1;
is the defocus aberration in unit of wavelength;
and
are coordinates in image plane;
and
are normalized pupil coordinates; and
is the normalized pupil function with a cubic phase mask and can be expressed as
Here
is the cubic parameter of the phase mask. Take
as an example. Stationary phase method [
7M. Born and E. Wolf, Principles of Optics (Pergamon, 1985).
] is used to obtain the approximated PSF as shown in
Eq. (3) and the details can be seen in Appendix A.
where
Figure 1(a)
displays the PSF representation when
and
, which is a piecewise function because of different stationary points exist in different PSF regions. Please refer to Appendix A for details.
Figure 1(b) gives the grey-scale map of the approximated PSF. Sampling frequency used here is
. Logarithm function of the PSF
is used in
Fig. 1(b) for the clarification. The black represents zero, while white represents the maximum value of the PSF. The discontinuities of the PSF at the boundaries are due to the use of the stationary method and will not affect the analysis of imaging characteristics [
5]. The boundaries are derived from
Eq. (4). Notice that the defocused PSF does not depend on the sign but on the absolute value of the defocus aberration.
Fig. 1 Approximated PSF of the wavefront coding system with a circular pupil. (a) Schematic diagram of the piecewise PSF function; (b) Grey-scale map of the log-PSF. Here and.
2.2 Focused PSF
Consider focused PSF, i.e.
. Then
Eq. (3) is simplified as
where,
,
,
. From
Eq. (7), three boundaries are written as
They form an isosceles right triangle shown in the red lines in
Fig. 2
. The right-angle sides are located on
and
axes, while the hypotenuse is located at the first quadrant. The length of right-angle sides are
.
Fig. 2 Boundaries of the focused PSF (in red) and the defocused PSF (in black). Here , the defocus aberration .
3. PSF analysis
According to
Eq. (3) and
Eq. (7), the defocused and the focused PSFs can be divided into six and two regions, respectively. The boundaries of defocused PSF are described in
Eq. (4) when equalities hold. Black lines in
Fig. 2 represent boundaries of the defocused PSF. Notice that the outer boundaries are determined by
Eq. (4a) and
Eq. (4e), as shown in black bold lines in
Fig. 2. Considering
Eq. (4e) and
Eq. (5), we obtain
Equation (9) can be further simplified as
, where
The variable
depends on
and
and reaches its maximum value of 1 when
.
takes the minimum when equalities hold in
Eqs. (4d),
(4e) or
Eqs. (4c),
(4e). Consider
Eq. (4d) and
Eq. (4e) first. We obtain
Substitute
Eq. (11) in
Eq. (10), then
. Thereby,
if
. Similarly,
when equalities hold in
Eqs. (4c),
(4e). Thereby, the boundaries of defocused PSF are written as
The differences between the defocused PSF and the focused PSF can be found by comparing
Eq. (8) and
Eq. (12). Firstly, defocus leads to position shift in both
and
directions. The offset is proportional to the square of the defocus aberration, and inversely proportional to the cubic parameter. Secondly, the PSF’s boundary expands as
increases. The increase in length of right angle side is about
. Thirdly, the defocus bends the hypotenuse of the boundaries and introduces boundary deformation.
Finally, the oscillations occur in most regions of the PSF, as shown in
Eq. (3). The oscillation frequencies
and
depend on
and
, respectively. Combining
Eq. (3),
Eq. (5) and
Eq. (6), oscillation frequencies can be written as
Thus, the frequency of oscillation increases as increases.
4. Defocus influences on decoded image
Defocus can also influence decoded images. The imaging process is usually described as the convolution of object
and the PSF
. Notice that convolution in space domain is the equivalent to multiplication in frequency domain. Therefore, the imaging process in frequency domain can be described as
Eq. (14), where
represents image, and
represents Fourier transform
Here we use
as the deconvolution kernel in digital decoding. The solution of
Eq. (14) is
where
represents decoded image and
represents inverse Fourier transform. Notice that
is used in optical encoding, while
is used in digital decoding. When consider the position shift and ignore other effects, the defocused PSF is described as
Using the translation property of Fourier transform [
8J. W. Goodman, Introduction to Fourier Optics (McGraw-Hill, 1996), Chap. 6.
], we obtain
where
and
are coordinates in frequency plane. Similarly,
Using the translation property of Fourier transform again, the decoded image is
Therefore, the defocus introduces position shift. The offset is related to the defocus aberrations used in optical encoding and digital decoding, and inversely proportional to the cubic parameter.
Furthermore, the defocused decoded PSF is a disc of confusion instead of an impulse, which leads to image blurring. This is attributed to the differences between the two PSFs used in encoding and decoding, such as boundary and oscillation frequency alteration introduced by defocus.
Figure 3
gives the decoded PSFs by using cubic parameter
and different defocus aberrations
and
. Here, Wiener filter [
9R. C. Gonzalez, R. E. Woods, and S. L. Eddins, Digital Image Processing Using Matlab (Prentice-Hall, 2004), Chap. 5.
] is used as the decoding algorithm and the focused PSF as the deconvolution kernel. It is apparent that the defocus results in position shift and image blurring, which is consistent with the analysis above.
Fig. 3 Decoded PSFs based on Wiener filter using focused PSF as the deconvolution kernel when and (a) ; (b) .
However, all of the influences can be ignored if the defocus aberration is very small compared to the cubic parameter. Then
Eq. (3) is simplified as
Eq. (7) when
. The details are displayed in Appendix B. In this way, the PSF is defocus invariant, i.e. the system is insensitive to defocus. One deconvolution kernel is efficient and effective in digital decoding to obtain sharp images.
5. Circular pupil and rectangular pupil
We further focus on the rectangular pupil system and the circular pupil system. The approximated PSF for the rectangular pupil system [
5] is described as
where
,
, and
,
Take
and
. The schematic diagram of the defocused PSF is shown in
Fig. 4(a)
and the grey-scale map of the defocused PSF is shown in
Fig. 4(b). Similarly, the logarithm function of the PSF is used here for the clarity. Sampling frequency used here is
. Notice that the boundaries of the PSF are determined by
Eq. (22) and shown in
Fig. 4(c). The black lines represent the boundaries of the defocused PSF. The black bold lines form the closed outer boundary, i.e.
Fig. 4 Approximated PSF of the wavefront coding system with a rectangular pupil. (a) Schematic diagram of the piecewise PSF function; (b) Grey-scale map of the defocused log-PSF; (c) Boundaries of the focused PSF (in red) and the defocused PSF (in black). Here , the defocus aberration .
The boundaries of the focused PSF are also given as a contrast, as shown in red lines in
Fig. 4(c).
Three similarities between rectangular pupil system and circular pupil system can be clearly observed. Firstly, the defocus leads to position shift along
and
directions. The offset is
. Secondly, the defocus leads to the boundary expansion and
increase in the length of side. Thirdly, the oscillation frequencies are the same as described in
Eq. (13). This can be explained that both oscillation frequencies of the PSFs depend on
and
, as shown in
Eq. (3) and
Eq. (21). There are also three differences between rectangular pupil system and circular pupil system. The first one is the shapes of the PSF’s boundaries. The rectangular pupil leads to a rectangular boundary, while the circular pupil does an isosceles right triangle boundary, which is obvious when comparing
Fig. 2 and
Fig. 4. The second one is the piece number of the PSF function. We compare
Eq. (3) and
Eq. (21) and find that the latter has six pieces while the former has five ones because of no region containing three stationary points in the former. Thirdly, the PSF boundaries remain rectangular even if
in the rectangular pupil system. In contrast, the defocus aberration causes the boundary deformation in the circular pupil system.
6. Conclusion
A method based on the stationary phase method is proposed to analyze the point spread function (PSF) of a circular pupil wavefront coding system and an approximated analytical expression of the defocused PSF was obtained. The absolute value of the defocus aberration affects the PSF and leads to the alteration of PSF in four aspects including position shift, boundary expansion, boundary deformation and oscillation frequency. The defocus also influenced the decoded image and caused position shift and image blurring. However, the influences on either PSF or decoded image can be omitted when the defocus aberration is much smaller than the cubic parameter. Three similarities (including position shift, boundary expansion and oscillation frequency) and three differences (including boundary shape, pieces number and boundary deformation) of PSF between the rectangular pupil system and the circular pupil system were detailed analyzed. In this way, the image characteristics of a cubic phase wavefront coding system with a circular pupil have been revealed clearly. It is helpful to analyze and design circular pupil wavefront coding systems.
Appendices
Appendix A: Deduction of the defocused PSF in a circular pupil wavefront coding system
The PSF function described in
Eq. (1) is rewritten as
where . The first and the second derivations of are
According to the stationary phase method, stationary points exist if and only if
Eq. (A3) is satisfied.
Let
Thus
, and
. Possible solutions of
Eq. (A3a) are
,
,
and
, where
Fig. A1 Color maps to distinguish regions containing different stationary points in (a): plane and (b): plane. Here .
Figure A1(a) uses color to distinguish regions containing different stationary points in
plane when
. All of the nonzero regions are located at the first quadrant because
. Consider positive defocus aberration, i.e.
first. The red region,
, has 4 stationary points,
,
,
and
. The yellow region,
, has 3 stationary points,
,
and
. The rose region,
, has 2 stationary points,
and
. The gray region,
, has 2 stationary points,
and
. The cyan region,
, has only 1 stationary point,
. If the defocus aberration is negative, i.e.
, then the subscripts, “01” and “02”, change places with each other in the text above. With
Eq. (A4) substituted in
Eq. (A6), the distribution of the stationary points in
plane is obtained and shown in
Fig. A1(b).
Equation (A1) is approximated as the sum of the stationary phase approximations evaluated at the stationary points [
7M. Born and E. Wolf, Principles of Optics (Pergamon, 1985).
].
where
are the stationary points existing in the area shown in
Fig. A1(a).
Substitute stationary points’ value in
Eq. (A7) and the PSF is described as
where, , , .
Appendix B: Proof of equivalence of Eq. (3) and Eq. (7) when
Consider
and rewrite
Eq. (5) as
Consequently,
Then consider boundaries of the defocused PSF described in
Eq. (4). Notice that
, and
Eq. (4a) can be simplified as
It is apparent that can be omitted when . Therefore, , , and can be approximated to be one set , i.e.
is described as
In other word, boundaries of the defocused PSF are simplified as
Eq. (8) when
.
As a consequence,
Eq. (3) can be simplified as
Eq. (7). In other words, the defocused PSF is approximated as the focused PSF when
.
Acknowledgments
This material is based upon work funded by
Zhejiang Provincial Natural Science Foundation of China under Grant No.
Y1110455,
Scientific Research Fund of Zhejiang Provincial Education Department under Grant No.
Y200909691, and
Science Foundation of Zhejiang Sci-Tech University (ZSTU) under Grant No.
0913849-Y.
References and links
1. | E. R. Dowski Jr and W. T. Cathey, “Extended depth of field through wave-front coding,” Appl. Opt. 34(11), 1859–1866 (1995). [CrossRef] [PubMed] |
2. | H. Zhao and Y. Li, “Optimized sinusoidal phase mask to extend the depth of field of an incoherent imaging system,” Opt. Lett. 35(2), 267–269 (2010). [CrossRef] [PubMed] |
3. | H. Zhao and Y. Li, “Optimized logarithmic phase masks used to generate defocus invariant modulation transfer function for wavefront coding system,” Opt. Lett. 35(15), 2630–2632 (2010). [CrossRef] [PubMed] |
4. | G. Muyo and A. R. Harvey, “Decomposition of the optical transfer function: wavefront coding imaging systems,” Opt. Lett. 30(20), 2715–2717 (2005). [CrossRef] [PubMed] |
5. | W. Zhang, Z. Ye, T. Zhao, Y. Chen, and F. Yu, “Point spread function characteristics analysis of the wavefront coding system,” Opt. Express 15(4), 1543–1552 (2007), http://www.opticsinfobase.org/abstract.cfm?&id=127217. [CrossRef] [PubMed] |
6. | S. Bagheri, P. E. Silveira, and D. P. de Farias, “Analytical optimal solution of the extension of the depth of field using cubic-phase wavefront coding. part I. reduced-complexity approximate representation of the modulation transfer function,” J. Opt. Soc. Am. A 25(5), 1051–1063 (2008). [CrossRef] [PubMed] |
7. | M. Born and E. Wolf, Principles of Optics (Pergamon, 1985). |
8. | J. W. Goodman, Introduction to Fourier Optics (McGraw-Hill, 1996), Chap. 6. |
9. | R. C. Gonzalez, R. E. Woods, and S. L. Eddins, Digital Image Processing Using Matlab (Prentice-Hall, 2004), Chap. 5. |