A novel optical readout infrared FPA imaging system with fiber reference channel

doi:10.1364/OE.20.009516

A novel optical readout infrared FPA imaging system with fiber reference channel

Xuhong Chu, Yuejin Zhao, Liquan Dong, Qian Jia, Lingqin Kong, Xiaomei Yu, Xiaohua Liu, Cheng Gong, and Yufeng Jin »View Author Affiliations

Optics Express, Vol. 20, Issue 9, pp. 9516-9522 (2012)
http://dx.doi.org/10.1364/OE.20.009516

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▸ Article Outline
– Abstract
1. Introduction
2. Methods and instruments
3. Experimental results
4. Conclusions
– References and links

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Abstract

A novel fiber reference optical readout method was proposed in the bi-material micro cantilever infrared imaging system, which consists of an infrared imaging channel, an optical readout channel and a fiber reference channel. The fiber reference channel is used to monitor the intensity fluctuation of the light source, and provide a signal to correct the distortion of the infrared images from the optical readout channel. Comparing with the typical optical readout method without any references, the noise equivalent temperature difference (NETD) of such an infrared imaging system with the fiber reference optical readout method can be reduced by about 33% and edges of the IR images become clearer.

1. Introduction

In 1996, Thomas Thundat in Oak Ridge National Lab invented a new infrared (IR) detector with voltage resistance micro cantilever beam, which showed the feasibility of using bi-material cantilever as infrared detector [1

P. I. Oden, P. G. Datskos, T. Thundat, and R. J. Warmack, “Uncooled thermal imaging using a piezoresistive microcantilever,” Appl. Phys. Lett. 69(21), 3277–3279 (1996). [CrossRef]

]. Therefrom many research institutions began to study the IR imaging system using the bi-material micro cantilever detector. Comparing with the thermoelectric-typed uncooled infrared imaging system, it eliminates the need for complex readout circuit, which makes it have extensive applied perspective [2

J. Varesi, J. Lai, T. Perazzo, Z. Shi, and A. Majumdar, “Photothermal measurements at picowatt resolution using uncooled micro-optomechanical sensors,” Appl. Phys. Lett. 71(3), 306–308 (1997). [CrossRef]

A. Rogalski, “Infrared detectors: Status and trends,” Prog. Quantum Electron. 27(2-3), 59–210 (2003). [CrossRef]

The NETD of the optical readout infrared FPA imaging system can be theoretically reduced to less than 5.7mK [4

J. Zhao, “High Sensitivity Photomechanical MW-LWIR Imaging using an Uncooled MEMS Microcantilever Array and Optical Readout,” Proc. SPIE 5783, 506–513 (2005). [CrossRef]

] or 5mK [5

H. Torun and H. Urey, “Uncooled Thermo-mechanical Detector Array with Optical Readout,” Proc. SPIE 5957, 59570O, 59570O-9 (2005). [CrossRef]

], however, it is usually almost 120mK [6

J. P. Salerno, “High Frame Rate Imaging Using Uncooled Optical Readout Photomechanical IR Sensor,” Proc. SPIE 6542, 65421D, 65421D-9 (2007). [CrossRef]

] or more in practice, which may be due to the fact that there are many factors could degrade the image quality, such as the undesired shape distortions in fabrication of the FPA, the aberrations of the lens, the impact of the filter, the stability of the illumination, and so on. In 2007, an optical readout platform using a knife-edge filter for detecting the bending of a bi-material micro cantilever array was established by Miao et al, and the NETD could be reduced to 50% [7

Z. Miao, Q. Zhang, Z. Guo, X. Wu, and D. Chen, “optical readout method for microcantilever array sensing and its sensitivity analysis,” Opt. Lett. 32(6), 594–596 (2007). [CrossRef] [PubMed]

]. In 2007, Liu et al pointed out that using holography illumination to compensate the shape distortions of the FPA in the optical readout infrared FPA imaging system was a feasible way to improve the system performance [8

M. Liu, Y. Zhao, L. Dong, X. Yu, X. Liu, M. Hui, J. You, and Y. Yi, “Holographic illumination in optical readout focal plane array infrared imaging system,” Opt. Lett. 34(22), 3547–3549 (2009). [CrossRef] [PubMed]

The former researchers mainly focused on the improvement of the filter and the compensation of the undesired shape distortions during fabrication of the FPA. In practice, the output of IR images are based on the gray-level difference, while the luminous intensity of the light source changes with time, which affects the image quality greatly. Generally, LED is often used as the light source and its luminous intensity alters owing to the fluctuations of ambient temperature, the electric current or other factors. To solve the problem mentioned above, this paper presents a new method which uses a fiber reference channel to monitor the fluctuation of the light source. The signal from the fiber reference channel is used to revise the images in real time, which can thus improve the NETD of the system.

It has been validated by means of experiment that the proposed method is effective in increasing the sensitivity of the proposed IR imaging system and improving its images quality.

2. Methods and instruments

2.1 Schematic diagram

The novel optical readout infrared FPA imaging system with fiber reference channel is a dual-light path system, as shown in Fig. 1 .

Fig. 1 The novel optical readout infrared FPA imaging system with fiber reference channel.

The system was composed of the IR imaging channel, the optical readout channel and the fiber reference channel. Comparing with the typical optical readout infrared FPA imaging system, the key point of the current system was the accretion of the fiber reference channel.

The IR lens collects the IR radiation of the object by focusing them on the FPA. For every micro cantilever pixel in the FPA, its absorber/reflector structure has one layer as an infrared absorber made by SiNx, and the other layer as a visible light reflector made by Au. Each pixel’s micro cantilevers of the FPA don’t deform when there is no infrared radiation focused on it, but its temperature rises after absorbing the infrared radiation, and the cantilevers deflect due to the difference between the thermal expansion coefficients of the two layer materials. For each pixel, the deflected angle θ is proportional to the incident IR radiation focused on it, namely, different IR radiations from different object points will make different deflected angle θ. The optical readout channel detects the deformation of the cantilevers of the FPA and the fiber reference channel monitors the intensity fluctuation of the light source and corrects its influence on the image.

In the optical readout channel, the light emitted from the light source is collimated by its illumination lens, and divided into two beams by a beam splitting prism. One of the beams is directed to the FPA for optical imaging, and the other is focused into the fiber for the reference. The rays reflected by the FPA are focused on the filter plane after passing through the prism again and the Fourier lens, then the filtered beam is projected onto CCD by the imaging lens. In the fiber reference channel, the reference rays emitted from the fiber directly illuminate a sub-area of CCD, pixels of which are divided into two areas. The great majority pixels of CCD receive the IR imaging from the optical readout channel, and the certain pixels receive the reference signals from the fiber reference channel, as shown in Fig. 2 .

Fig. 2 Image region of CCD.

The energy that the great majority pixels of CCD receive is E_a when there is no deformation on the micro cantilever of the FPA. It will change to E_s when the cantilever of the FPA deflects due to the object IR radiation. Then the energy variation that the great majority pixels of CCD detect is ∆E = E_a-E_s under the two conditions. The image processing system displays ∆E on the monitor in the form of gray-level difference.

∆E is always caused by not only the object IR radiation but also other factors, such as the fluctuation of the light source intensity. In order to get the energy variation caused by the object IR radiation only, the energy variation of the fluctuation of the light source intensity must be deducted. The fiber reference channel is used to monitor the intensity fluctuation of the light source and provides a signal to deduce the effect of the fluctuation of the light source on the ∆E and improve the image quality of the system.

2.2 Principles

From the analysis above, we know that the display image is a gray-level image, and the gray-level is proportional to the energy difference ∆E that each pixel receives, giving

Δ E = E_{a} - E_{s}

(1)

where E_a is the energy that the IR image area of CCD received when there’s no object infrared radiation, and E_s is the energy when there’s object infrared radiation.

In practice, the object IR radiation is blocked at the time t₀ and the energy that the IR image area of CCD receives is E₀. The object IR radiation is let in at the time t and the energy that the IR image area of CCD receives is E_t. Substituting E_t and E₀ for E_s and E_a, we get

Δ E_{0} = E_{0} - E_{t}

(2)

The light source of this system is a green LED and its luminous intensity always changes when the ambient temperature, the electric current or any other factors alter, which leads to the variation between ∆E and ∆E₀, as shown in Fig. 3 ,

Fig. 3 Energy on the spectrum plane.

∆E_r in Fig. 3 is the real IR image caused by the object IR radiation, while ∆E_e is generated by the fluctuation of the light source. If ∆E₀ is used as the IR image, the IR image will be amplified or neutralized owing to the existence of ∆E_e, which leads to the anamorphose. So we must get ∆E_r from ∆E₀. The fiber reference channel is used to achieve this goal.

Supposing that the energy from the fiber reference channel is E_q0 at the time t₀ and E_qt at the time t, when the object IR radiation is blocked, the following equation can be obtained

\frac{E_{q 0}}{E_{q t}} = \frac{E_{0}}{E_{a t}}

(3)

Where E_at is the energy from the optical readout channel at the time t, when the object IR radiation is blocked.

Since E_q0 and E_qt can be gained directly from the fiber reference channel and E₀ can be gained directly from the optical readout channel, according to Eq. (3), one can get

E_{a t} = \frac{E_{q t}}{E_{q 0}} \times E_{0}

(4)

From Eq. (1), the real gray-level value at the time t can be expressed as

Δ E_{t} = E_{a} - E_{s} = E_{a t} - E_{t}

(5)

Substituting Eq. (4) into Eq. (5), we get

Δ E_{t} = \frac{E_{q t}}{E_{q 0}} \times E_{0} - E_{t}

(6)

Normalizing ∆E according to the time t₀, leads to

Δ E = \frac{E_{q 0}}{E_{q t}} (\frac{E_{q t}}{E_{q 0}} \times E_{0} - E_{t}) = E_{0} - \frac{E_{q 0}}{E_{q t}} \times E_{t}

(7)

Compared Eq. (7) with Eq. (2), it can be seen the latter one has an extra modifying factor (E_q0/E_qt). The factor can be used to revise the background signal at the time t to the time t₀, in order to eliminate the effect caused by the energy difference between the time t₀ and t due to the light source luminous intensity changes, such as ∆E_e in Fig. 3.

3. Experimental results

The infrared imaging system was set up according to Fig. 1, and we got infrared images shown in Fig. 4 and Fig. 5 .

Fig. 4 Images of an electric iron three meters away.

Fig. 5 Images of a scissors three meters away in front of the background at 70°C.

Figure 4 shows the images of an electric iron three meters away. Figure 4(a) is calculated on the basis of Eq. (2) and Fig. 4(b) is calculated on the basis of Eq. (7).

Figure 5 shows the image of a scissors three meters away in front of the background at 70°C . Figure 5(a) is calculated on the basis of Eq. (2) and Fig. 5(b) is calculated on the basis of Eq. (7).

From Fig. 4 and Fig. 5, it can be seen that the images revised by the fiber reference method have better contrast and clearer outline than the uncorrected ones.

3.1 Sensitivity

The NETD represents the detection sensitivity of the IR imaging system, which is one of the key qualifications of the IR imaging system. It can be expressed as

N E T D = Δ T \times \frac{V_{n}}{V_{s}}

(8)

where ∆T is the temperature difference, V_s is the peak voltage of the signal, and V_n is the RMS value of the noise.

In this system, the peak voltage of the signal V_s is in direct ratio with the corresponding gray-level value of the image G_max. The RMS voltage of the noise V_n is proportional to the RMS offset of the noise gray-level value G_n. Thus, substituting G_max and G_n for V_s and V_n, leads to

N E T D = Δ T \times \frac{V_{n}}{V_{s}} = Δ T \times k \times \frac{G_{n}}{G_{\max}}

(9)

where k is a coefficient.

By picking the parameters from Fig. 4(a) and Fig. 4(b), the corresponding value of NETD can be obtained, as shown in Table 1 , from which it can be seen that the NETD values was reduced about 33% by using the fiber reference method.

Table 1 Calculated Values of NETD

		Without fiber reference			With fiber reference
		Value	Average		Value	Average
	G_max1	128		122	77	81.7
G_max	G_max2	121			88
	G_max3	117			80
	G_n1	11		12.3	13	12.3
G_n	G_n2	14			11
	G_n3	12			13
NETD		9.92 × ∆T × k			6.64 × ∆T × k

3.2 Image definition

The original angles θ₀ of the different micro cantilever of the FPA aren’t entirely consistent owing to the processing technique. Thus, the Fraunhofer diffraction pattern of the different unit of the FPA on the spectrum plane doesn’t overlap completely, as shown in Fig. 6 .

Fig. 6 Energy from different unit of the FPA on the spectrum plane.

Since the reflected light of each FPA unit that enters into the filter hole isn’t the same, the impact of ∆E_e on ∆E_r is different when the light source intensity changes, as shown in Fig. 7 .

Fig. 7 Impact of different unit of the FPA on the spectrum plane.

We can see that impact of ∆E_e on ∆E_r in Fig. 7(b) is much more than that in Fig. 7(a). Therefore, even if the object IR radiation is the same, the light source intensity fluctuation will held a greater influence on the Fig. 7(b) than the Fig. 7(a), which results to the distortion of the energy variation on the imaging plane and the edges of the images will inevitably appear distorted and fuzzy. The adoption of the fiber reference channel eliminates the impact of the light fluctuation ∆E_e, thus, the edges of the IR images become clearer and the gray-level values are more uniform such as in Fig. 5.

4. Conclusions

In summary, a new approach named “the novel optical readout infrared FPA imaging system with fiber reference channel” was presented. Comparing with the conventional optical readout method, this method can effectively eliminate the influence of the light fluctuation and other miscellaneous light, increase the sensitivity of the system and improves the image quality. The NETD can be reduced by 33%, and the edges of the IR images become clearer and the gray-level value is more uniform.

Acknowledgments

This work was supported by the State Key Program of National Natural Science Foundation of China (No. 61036006), the National Natural Science Foundation of China (No. 61177094) and the Doctoral Program Foundation of Institutions of Higher Education of China (No. 20091101120022). The authors would like to thank Dr. Jing Sui from The Mind Research Network for her great suggestion to the paper.

References and links

1.	P. I. Oden, P. G. Datskos, T. Thundat, and R. J. Warmack, “Uncooled thermal imaging using a piezoresistive microcantilever,” Appl. Phys. Lett. 69(21), 3277–3279 (1996). [CrossRef]
2.	J. Varesi, J. Lai, T. Perazzo, Z. Shi, and A. Majumdar, “Photothermal measurements at picowatt resolution using uncooled micro-optomechanical sensors,” Appl. Phys. Lett. 71(3), 306–308 (1997). [CrossRef]
3.	A. Rogalski, “Infrared detectors: Status and trends,” Prog. Quantum Electron. 27(2-3), 59–210 (2003). [CrossRef]
4.	J. Zhao, “High Sensitivity Photomechanical MW-LWIR Imaging using an Uncooled MEMS Microcantilever Array and Optical Readout,” Proc. SPIE 5783, 506–513 (2005). [CrossRef]
5.	H. Torun and H. Urey, “Uncooled Thermo-mechanical Detector Array with Optical Readout,” Proc. SPIE 5957, 59570O, 59570O-9 (2005). [CrossRef]
6.	J. P. Salerno, “High Frame Rate Imaging Using Uncooled Optical Readout Photomechanical IR Sensor,” Proc. SPIE 6542, 65421D, 65421D-9 (2007). [CrossRef]
7.	Z. Miao, Q. Zhang, Z. Guo, X. Wu, and D. Chen, “optical readout method for microcantilever array sensing and its sensitivity analysis,” Opt. Lett. 32(6), 594–596 (2007). [CrossRef] [PubMed]
8.	M. Liu, Y. Zhao, L. Dong, X. Yu, X. Liu, M. Hui, J. You, and Y. Yi, “Holographic illumination in optical readout focal plane array infrared imaging system,” Opt. Lett. 34(22), 3547–3549 (2009). [CrossRef] [PubMed]

OCIS Codes
(110.0110) Imaging systems : Imaging systems
(110.3080) Imaging systems : Infrared imaging
(230.4685) Optical devices : Optical microelectromechanical devices

ToC Category:
Imaging Systems

History
Original Manuscript: December 14, 2011
Revised Manuscript: February 3, 2012
Manuscript Accepted: February 28, 2012
Published: April 11, 2012

Citation
Xuhong Chu, Yuejin Zhao, Liquan Dong, Qian Jia, Lingqin Kong, Xiaomei Yu, Xiaohua Liu, Cheng Gong, and Yufeng Jin, "A novel optical readout infrared FPA imaging system with fiber reference channel," Opt. Express 20, 9516-9522 (2012)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-20-9-9516

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References

P. I. Oden, P. G. Datskos, T. Thundat, and R. J. Warmack, “Uncooled thermal imaging using a piezoresistive microcantilever,” Appl. Phys. Lett.69(21), 3277–3279 (1996). [CrossRef]
J. Varesi, J. Lai, T. Perazzo, Z. Shi, and A. Majumdar, “Photothermal measurements at picowatt resolution using uncooled micro-optomechanical sensors,” Appl. Phys. Lett.71(3), 306–308 (1997). [CrossRef]
A. Rogalski, “Infrared detectors: Status and trends,” Prog. Quantum Electron.27(2-3), 59–210 (2003). [CrossRef]
J. Zhao, “High Sensitivity Photomechanical MW-LWIR Imaging using an Uncooled MEMS Microcantilever Array and Optical Readout,” Proc. SPIE5783, 506–513 (2005). [CrossRef]
H. Torun and H. Urey, “Uncooled Thermo-mechanical Detector Array with Optical Readout,” Proc. SPIE5957, 59570O, 59570O-9 (2005). [CrossRef]
J. P. Salerno, “High Frame Rate Imaging Using Uncooled Optical Readout Photomechanical IR Sensor,” Proc. SPIE6542, 65421D, 65421D-9 (2007). [CrossRef]
Z. Miao, Q. Zhang, Z. Guo, X. Wu, and D. Chen, “optical readout method for microcantilever array sensing and its sensitivity analysis,” Opt. Lett.32(6), 594–596 (2007). [CrossRef] [PubMed]
M. Liu, Y. Zhao, L. Dong, X. Yu, X. Liu, M. Hui, J. You, and Y. Yi, “Holographic illumination in optical readout focal plane array infrared imaging system,” Opt. Lett.34(22), 3547–3549 (2009). [CrossRef] [PubMed]

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