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Ultrathin arrayed camera for high-contrast near-infrared imaging

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Abstract

We report an ultrathin arrayed camera (UAC) for high-contrast near infrared (NIR) imaging by using microlens arrays with a multilayered light absorber. The UAC consists of a multilayered composite light absorber, inverted microlenses, gap-alumina spacers and a planar CMOS image sensor. The multilayered light absorber was fabricated through lift-off and repeated photolithography processes. The experimental results demonstrate that the image contrast is increased by 4.48 times and the MTF 50 is increased by 2.03 times by eliminating optical noise between microlenses through the light absorber. The NIR imaging of UAC successfully allows distinguishing the security strip of authentic bill and the blood vessel of finger. The ultrathin camera offers a new route for diverse applications in biometric, surveillance, and biomedical imaging.

© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. Introduction

Near-infrared (NIR) imaging exhibits functional roles in various applications such as surveillance [1,2], biometric [35], or biomedical imaging [6,7]. The NIR imaging allows the recognition of vascular patterns in a hand or a finger to identify personal information [8,9], and the observation of wound recovery [10]. Recently, demands for miniaturization of NIR cameras are increasing to immediately observe NIR data through wearable and handheld smart devices [1114]. For instance, the camera of a wearable device for eye-tracking requires miniaturization as well as near-distance imaging. However, conventional visible or NIR cameras include a mechanical assembled lens system comprising multi-stacks of lenses, and the lens structure prevents reducing the overall thickness of NIR camera [15]. Microlens arrays (MLAs) based imaging systems can diminish the total track length (TTL) of camera due to the short focal length and small optical aberrations of MLAs [1618]. In addition, these systems can provide multifocal images through the extended depth-of-field of diverse microlenses with high-to-low numerical aperture [19].

A light absorber is a crucial structure in MLAs to block the optical crosstalk between the microlenses, and acquire high-resolution and high-contrast images [20]. This light absorber can be fabricated through processes such as UV patterning, mechanical processing, and replica molding [21,22]. Unlike other methods, UV patterning serves as an important role for fabricating the light absorber with an ultrathin thickness as well as aligning the optical axis between an aperture on the light absorber layer and a microlens [23]. However, UV patternable black polymers have some limitations in blocking NIR light, whereas the polymers prevent visible light efficiently [24]. The mechanically fabricated light absorber blocks the NIR through thick opaque materials, while an additional complex process needs to be performed to align the optical axis between the aperture arrays and MLAs [2].

Here we report an ultrathin arrayed camera (UAC) for high-contrast NIR imaging [Fig. 1(a)]. The UAC features multilayered composite aperture arrays (MCAAs), inverted-microlens arrays (iMLAs), and rectangular spacers on a CMOS active pixel image sensor (Sony IMX 219, pixel size: 1.12 µm × 1.12 µm). The MCAAs, fabricated by the laminated structure of metal and polymer, offer efficient light blocking in a wide spectrum of visible to NIR range. The metal layer of MCAAs dramatically reduces the transmission of NIR, and that of polymer layers suppress the reflection causing image artifacts. The UAC with MCAAs can also reduce the optical noise between microlenses and thus increase the image resolution as well as the image contrast. Array images captured by the UAC can be reconstructed into a single image to improve the image quality through an image processing algorithm.

 figure: Fig. 1.

Fig. 1. Ultrathin arrayed camera (UAC) for high-contrast NIR imaging. (a) A schematic illustration of UAC, which contains a NIR filter, a window glass, multilayered-composite aperture arrays (MCAAs), inverted-microlens arrays (iMLAs), gap-alumina spacers and an image sensor. The MCAAs reduce optical crosstalk entering between the microlenses as well as optical noise reflected by the image sensor surface. (b) The microfabrication steps of UAC. The MCAAs were fabricated by using a lift-off process and repeated photolithography. The iMLAs were formed by using the thermal reflow of photolithographic defined patterns. The MCAAs and iMLAs were fully packaged with a single CMOS image sensor through gap-spacers. (c) A scanning electron microscopy (SEM) image of iMLAs. (d) A photograph of a fully packaged UAC.

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2. Microfabrication of Ultrathin Arrayed Camera

The microfabrication steps for the UAC are schematically illustrated in Fig. 1(b). A lift-off resist (LOR, MicroChem Corp.) and photoresist resist (AZ GXR-601, AZ Electronic Materials.) were first spin-coated onto a 4-inch borosilicate wafer substrate and then photolithographically defined by using the MA-6 mask aligner. A 100 nm thick Chromium (Cr) film was deposited on the pattern and the remaining resists were removed through a resist stripper. A transparent polymer (SU-8 2025), 25 µm in thickness, was coated on the metal pattern layer and a black polymer (GMC 1040, Gersteltec), 5 µm in thickness, was photolithographically patterned. The repeated patterning process of transparent and black photoresist was performed to form multi-layer structures, i.e., the 3-layers of transparent photoresist and the 2-layers of black photoresist. A positive-tone photoresist (AZ9260, MicroChem Corp.), 25 µm in thickness, was defined on the multi-layer structure, and the microlens shape was formed by upside-down reflow process at 180°C for 30 min on a hot plate. The focal length of fabricated microlens is 510 µm, and the radius of curvature is 270 µm. Alumina spacers were stacked at the height of microlens focal length on a single CMOS image sensor. The fabricated microlens plate was finally packaged with the image sensor (Sony IMX 219) by using a flip-chip bonder and finally a NIR band-pass filter was integrated on the packaged camera. Figure 1(c) shows a scanning electron micrograph of iMLAs. Figure 1(d) represents an optical image of the fully packaged UAC. The UAC has the f-number of 1.7 with the microlens diameter of 300 µm and the TTL of 1.07 mm including a window glass.

3. MCAAs Characterization

The light blocking properties of MCAAs were measured by using a spectrometer and a confocal laser scanning microscope (CLSM) with a collimated broadband light source (Thorlabs, SLS201L/M, λ: 360 nm ∼ 2,600 nm). The experimental results show that black polymer has transmittance less than 5% in the visible range and higher than 80% in the NIR range [Fig. 2(a-i)]. The Cr layer blocks a broadband spectrum of light whereas it exhibits the reflectance higher than 60% [Fig. 2(a-ii)]. The stacked multilayers of metal and polymer can prevent the transmission of broadband light but also reduce the reflectance below 30% [Fig. 2(a-iii)]. The experimental results demonstrate that the MCAAs effectively block light as well as substantially reduce the reflectance. The cross-sectional images of NIR beam passing were captured through the CLSM to observe the optical crosstalk between the MLAs. The optically sectioned images of iMLAs with the MCAAs also exhibit the clear reduction of optical crosstalk between microlenses unlike that without the MCAAs Figs. 2(b) and 2(c)]. The corresponding intensity profile also exhibits sharp peaks without optical noise between the peaks [Fig. 2(d)]. The experimental results demonstrate the MCAAs clearly remove the optical crosstalk, which is about 50% of main peak intensity, at broadband wavelengths between 360 nm and 2,600 nm. The results indicate that the metal layers in the MCAAs effectively blocks the NIR noise.

 figure: Fig. 2.

Fig. 2. Light blocking efficiency of MCAAs. (a) The normalized spectral absorbance, transmittance, and reflectance of (i) the polymer layers only, (ii) the Cr layer only, and (iii) the MCAAs. The MCAAs reduce the transmittance by using the Cr layer and diminish the reflectance through the black polymer layers. Cross-sectional images of NIR beam passing through the iMLAs (b) without the MCAAs, and (c) with the MCAAs. The optically sectioned image was obtained by using a confocal laser scanning microscope (CLSM). (d) The corresponding measured intensity of cross-sectional images. Optical noises between the sharp peaks were reduced by the MCAAs.

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4. High-Contrast NIR Imaging

The captured images of USAF 1951 target, located at 5 cm from the camera, clearly demonstrate that the UAC with the MCAAs offers higher contrast than that without the MCAAs [Figs. 3(a) and 3(b)]. For experiments, the NIR light (3W, λ: 850 nm) was irradiated from the back-side of the negative USAF 1951 target. The Michelson contrast and the measured modulation transfer function (MTF) were measured to compare quantitatively imaging performances by using the MCAAs. The calculated Michelson contrast of the UAC without the MCAAs exhibits 0.114 and that with the MCAAs shows 0.511, which represents the image contrast is clearly increased by 4.48 times [Fig. 3(c)]. The MTF 50 is also increased by 2.03 times, i.e., 0.065 cycles/mm for without the MCAAs and 0.132 cycles/mm for with the MCAAs [Fig. 3(d)]. The resolution and uniformity of array images can be potentially further improved by using an image sensor optimized for the iMLAs. The experimental results demonstrate that the image resolution as well as the image contrast are clearly increased by the MCAAs. The Cr layer between the microlenses can generate image artifacts due to the light reflected from the image sensor [Fig. 3(e)]. In contrast, the black polymer under the Cr layer can remove image artifacts by inhibiting the reflection. Figure 3(f) exhibits image artifacts by the reflection of Cr layer only, whereas Fig. 3(g) shows the clear array images of cone without image artifacts due to reduced reflectivity through the MCAAs.

 figure: Fig. 3.

Fig. 3. High-contrast NIR imaging through the UAC with the MCAAs. Captured images through the UAC (a) without the MCAAs, and (b) with the MCAAs. The USAF 1951 target located 5 cm from the UAC. (c) The corresponding intensity profiles of captured images to calculate contrasts. (d) The MTF curves of captured images to compare resolution improvement after applying the MCAAs. (e) A schematic illustration of image artifacts due to the reflection of Cr layer. “Cone” array images captured by the UAC (f) with Cr layer only, and (g) with the MCAAs. Yellow arrows show image artifacts due to the reflection. Clear array images without the image artifacts were captured after applying the MCAAs.

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5. NIR Imaging Applications

Array images from the UAC were captured for a target object of ‘United States five-dollar bill’ in the NIR light source. The UAC successfully observes security strips, i.e., lines observed only in the authentic bill to discriminate counterfeit bills through NIR imaging. The array images were finally merged into a single high-resolution image by using the super-resolution algorithm [25]. The reconstructed image shows the image sharpness and contrast higher than the single channel image of UAC [Figs. 4(a) and 4(b)]. The MTF 50 value for the merged image is 0.204 cycles/mm, which represents 51% of that for a commercialized compact camera (Raspberry Pi NOIR camera V2). Figure 4(c) shows the image of authentic bill captured by the UAC in the visible region and Fig. 4(d) exhibits the printed counterfeit bill in the NIR light. The experimental results clearly demonstrate that the security strips are only observed in the NIR imaging of authentic bill. The UAC features a short focal length, allowing image capturing with all-in-focus regardless of object distances. To observe the position of pupil in an eye, the pupil images were captured at a distance of 3 cm between the camera and the eye. The experimental results show that the UAC captures clear eye images in the NIR lights and observe the displacement of pupil [Figs. 4(e) and 4(f)]. The results indicate that the UAC can be effectively applied to wearable devices requiring eye-tracking. In order to observe the finger veins through the UAC, the NIR source was irradiated on the backside of a finger [Fig. 4(g)]. The finger vein was captured at distance of 5 cm from the UAC. The single channel of UAC offers the image of finger vein patterns and the merged result provides the high-contrast image of finger vein patterns than the single channel [Figs. 4(h) and 4(i)]. In addition, the image sharpness was increased by using a sharpness enhancement filter in order to display the clear distinction of vein patterns [Fig. 4(j)].

 figure: Fig. 4.

Fig. 4. NIR imaging applications through the UAC. (a) An image acquired by the single channel of UAC before the super-resolution imaging. (b) A reconstructed image by combining captured array images. (c) The image of five-dollar bill in the visible light. (d) The captured NIR image of printed counterfeit bill. The security strips were only observed in NIR imaging of authentic bills. The captured images of eye gazing to (e) the front and (f) the side through the UAC. (g) A schematic illustration of the experimental setup to observe finger vein. (h) A finger vein image captured through the single channel of UAC. (i) A reconstructed image through super-resolution NIR imaging. (j) The edge enhanced image to emphasize vein.

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6. Conclusions

In summary, this work has successfully demonstrated an ultrathin arrayed camera for high-contrast NIR imaging. The MCAAs containing multilayers of metal and polymer effectively reduce the transmittance and reflection of NIR light. The novel configuration allows effectively reducing the NIR optical crosstalk between microlens arrays. The UAC with the MCAAs offers 4.5 times higher in the image contrast and 2 times higher in the MTF50, compared to that without the MCAAs. The artifact images resulting from the reflection of Cr layer were also eliminated by using the black polymer layers. The high-contrast NIR images of counterfeit bill discrimination and finger vessel were finally obtained through the image reconstruction of array images. This ultrathin camera for high-contrast NIR imaging can provide novel directions for biometric, surveillance or biomedical applications.

Funding

National Research Foundation of Korea (No. 2016R1A2B301306115); Ministry of Health and Welfare (No. HI16C1111); Defence Acquisition Program Administration (Critical Technology R&D program); LIG Nex1 Co., Ltd..

Disclosures

The authors declare no conflicts of interest.

References

1. X. Liu, J. Chang, W. L. Chen, K. Y. Fan, Y. Zhong, B. Zhang, and X. Z. Gong, “A dynamic foveated infrared imager for surveillance,” Opt Laser Eng 124, 105825 (2020). [CrossRef]  

2. C. Gassner, J. Dunkel, A. Oberdorster, and A. Bruckner, “Compact wide-angle array camera for presence detection,” Moems and Miniaturized Systems Xvii10545, 10 (2018).

3. R. S. Ghiass, O. Arandjelovic, A. Bendada, and X. Maldague, “Infrared face recognition: A comprehensive review of methodologies and databases,” Pattern Recogn 47(9), 2807–2824 (2014). [CrossRef]  

4. W. Kim, J. M. Song, and K. R. Park, “Multimodal Biometric Recognition Based on Convolutional Neural Network by the Fusion of Finger-Vein and Finger Shape Using Near-Infrared (NIR) Camera Sensor,” Sensors 18(7), 2296 (2018). [CrossRef]  

5. Z. Xie, S. Zhang, X. Yu, and G. Liu, “Infrared and visible face fusion recognition based on extended sparse representation classification and local binary patterns for the single sample problem,” J. Opt. Technol. 86(7), 408–413 (2019). [CrossRef]  

6. G. S. Hong, A. L. Antaris, and H. J. Dai, “Near-infrared fluorophores for biomedical imaging,” Nat. Biomed. Eng. 1(1), 0010 (2017). [CrossRef]  

7. F. Ding, Y. B. Zhan, X. J. Lu, and Y. Sun, “Recent advances in near-infrared II fluorophores for multifunctional biomedical imaging,” Chem. Sci. 9(19), 4370–4380 (2018). [CrossRef]  

8. J. Y. Bok, K. H. Suh, and E. C. Lee, “Detecting Fake Finger-Vein Data Using Remote Photoplethysmography,” Electronics-Switz 8(9), 1016 (2019). [CrossRef]  

9. S. Merlo, V. Bello, E. Bodo, and S. Pizzurro, “A VCSEL-Based NIR Transillumination System for Morpho-Functional Imaging,” Sensors 19(4), 851 (2019). [CrossRef]  

10. K. Kaile and A. Godavarty, “Development and Validation of a Smartphone-Based Near-Infrared Optical Imaging Device to Measure Physiological Changes In-Vivo,” Micromachines 10(3), 180 (2019). [CrossRef]  

11. D. Toslak, C. G. Liu, M. N. Alam, and X. C. Yao, “Near-infrared light-guided miniaturized indirect ophthalmoscopy for nonmydriatic wide-field fundus photography,” Opt. Lett. 43(11), 2551–2554 (2018). [CrossRef]  

12. J. Behmann, K. Acebron, D. Emin, S. Bennertz, S. Matsubara, S. Thomas, D. Bohnenkamp, M. T. Kuska, J. Jussila, H. Salo, A. K. Mahlein, and U. Rascher, “Specim IQ: Evaluation of a New, Miniaturized Handheld Hyperspectral Camera and Its Application for Plant Phenotyping and Disease Detection,” Sensors 18(2), 441 (2018). [CrossRef]  

13. F. Liu, H. Bian, F. Zhang, Q. Yang, C. Shan, M. J. Li, X. Hou, and F. Chen, “IR Artificial Compound Eye,” Adv. Opt. Mater. 8(4), 2070013 (2020). [CrossRef]  

14. J. Z. Wang, G. Y. Zhang, and J. D. Shi, “Pupil and Glint Detection Using Wearable Camera Sensor and Near-Infrared LED Array,” Sensors 15(12), 30126–30141 (2015). [CrossRef]  

15. L. Yu, “Upgrade of a UV-VIS-NIR imaging spectrometer for the coastal ocean observation: concept, design, fabrication, and test of prototype,” Opt. Express 25(13), 15526–15538 (2017). [CrossRef]  

16. A. Bruckner, J. Duparre, R. Leitel, P. Dannberg, A. Brauer, and A. Tunnermann, “Thin wafer-level camera lenses inspired by insect compound eyes,” Opt. Express 18(24), 24379–24394 (2010). [CrossRef]  

17. D. Keum, K. W. Jang, D. S. Jeon, C. S. H. Hwang, E. K. Buschbeck, M. H. Kim, and K. H. Jeong, “Xenos peckii vision inspires an ultrathin digital camera,” Light-Sci Appl 7(1), 80 (2018). [CrossRef]  

18. T. Chung, Y. Lee, S. P. Yang, K. Kim, B. H. Kang, and K. H. Jeong, “Mining the Smartness of Insect Ultrastructures for Advanced Imaging and Illumination,” Adv Funct Mater 28(24), 1705912 (2018). [CrossRef]  

19. S. I. Bae, K. Kim, S. Yang, K. W. Jang, and K. H. Jeong, “Multifocal microlens arrays using multilayer photolithography,” Opt. Express 28(7), 9082–9088 (2020). [CrossRef]  

20. K. Kim, K.-W. Jang, and K.-H. Jeong, “Ultrathin Compound Eye Camera for Super-Resolution Far-Field Imaging Using Light Absorbing Multiple Layers,” in 2019 IEEE 32nd International Conference on Micro Electro Mechanical Systems (MEMS), (IEEE, 2019), 942–945.

21. Y. M. Song, Y. Z. Xie, V. Malyarchuk, J. L. Xiao, I. Jung, K. J. Choi, Z. J. Liu, H. Park, C. F. Lu, R. H. Kim, R. Li, K. B. Crozier, Y. G. Huang, and J. A. Rogers, “Digital cameras with designs inspired by the arthropod eye,” Nature 497(7447), 95–99 (2013). [CrossRef]  

22. M. J. Moghimi, J. Fernandes, A. Kanhere, and H. R. Jiang, “Micro-Fresnel-Zone-Plate Array on Flexible Substrate for Large Field-of-View and Focus Scanning,” Sci. Rep. 5(1), 15861 (2015). [CrossRef]  

23. K. Kim, K. W. Jang, J. K. Ryu, and K. H. Jeong, “Biologically inspired ultrathin arrayed camera for high-contrast and high-resolution imaging,” Light-Sci Appl 9(1), 28 (2020). [CrossRef]  

24. K. Kim, K.-W. Jang, S.-I. Bae, and K.-H. Jeong, “Ultrathin digital camera for high-contrast NIR imaging,” in 2019 International Conference on Optical MEMS and Nanophotonics (OMN), (IEEE, 2019), 60–61.

25. S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, “Fast and robust multiframe super resolution,” IEEE Trans. on Image Process. 13(10), 1327–1344 (2004). [CrossRef]  

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Figures (4)

Fig. 1.
Fig. 1. Ultrathin arrayed camera (UAC) for high-contrast NIR imaging. (a) A schematic illustration of UAC, which contains a NIR filter, a window glass, multilayered-composite aperture arrays (MCAAs), inverted-microlens arrays (iMLAs), gap-alumina spacers and an image sensor. The MCAAs reduce optical crosstalk entering between the microlenses as well as optical noise reflected by the image sensor surface. (b) The microfabrication steps of UAC. The MCAAs were fabricated by using a lift-off process and repeated photolithography. The iMLAs were formed by using the thermal reflow of photolithographic defined patterns. The MCAAs and iMLAs were fully packaged with a single CMOS image sensor through gap-spacers. (c) A scanning electron microscopy (SEM) image of iMLAs. (d) A photograph of a fully packaged UAC.
Fig. 2.
Fig. 2. Light blocking efficiency of MCAAs. (a) The normalized spectral absorbance, transmittance, and reflectance of (i) the polymer layers only, (ii) the Cr layer only, and (iii) the MCAAs. The MCAAs reduce the transmittance by using the Cr layer and diminish the reflectance through the black polymer layers. Cross-sectional images of NIR beam passing through the iMLAs (b) without the MCAAs, and (c) with the MCAAs. The optically sectioned image was obtained by using a confocal laser scanning microscope (CLSM). (d) The corresponding measured intensity of cross-sectional images. Optical noises between the sharp peaks were reduced by the MCAAs.
Fig. 3.
Fig. 3. High-contrast NIR imaging through the UAC with the MCAAs. Captured images through the UAC (a) without the MCAAs, and (b) with the MCAAs. The USAF 1951 target located 5 cm from the UAC. (c) The corresponding intensity profiles of captured images to calculate contrasts. (d) The MTF curves of captured images to compare resolution improvement after applying the MCAAs. (e) A schematic illustration of image artifacts due to the reflection of Cr layer. “Cone” array images captured by the UAC (f) with Cr layer only, and (g) with the MCAAs. Yellow arrows show image artifacts due to the reflection. Clear array images without the image artifacts were captured after applying the MCAAs.
Fig. 4.
Fig. 4. NIR imaging applications through the UAC. (a) An image acquired by the single channel of UAC before the super-resolution imaging. (b) A reconstructed image by combining captured array images. (c) The image of five-dollar bill in the visible light. (d) The captured NIR image of printed counterfeit bill. The security strips were only observed in NIR imaging of authentic bills. The captured images of eye gazing to (e) the front and (f) the side through the UAC. (g) A schematic illustration of the experimental setup to observe finger vein. (h) A finger vein image captured through the single channel of UAC. (i) A reconstructed image through super-resolution NIR imaging. (j) The edge enhanced image to emphasize vein.
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