1. Bio-inspired design: nonlinear digital pixels for multiple-tier processes (invited paper) SPIE Nano/Bio/Info-Tech Sensors and Systems March 2013 O. Skorka, A. Mahmoodi, J. Li, and D. Joseph Electrical and Computer Engineering University of Alberta, Edmonton, AB, Canada

2. Outline Introduction Bio-inspired design Nonlinear response Digital pixels Multiple-tier processes Conclusion 2

3. Introduction Carver Mead, who cofounded Foveon in 1997, was a pioneer for bio-inspired electronics in the 1980s. His work on the “silicon retina” continues to inspire researchers in the image sensor community. Yet, a design inspired by biological systems too literally does not guarantee comparable functionality. The approach presented here is more concerned with bio-inspired performance than structure or form. We use the human eye’s capabilities as benchmarks to motivate and direct research on image sensors, while leveraging existing and emerging technologies. 3

4. Bio-inspired design ParameterType 1.Power consumptionPwC 2.Visual fieldVF Geometric 3.Spatial resolutionSR 4.Temporal resolutionTR 5. Peak signal-to-noise-and- distortion ratio PSNDR Signal and noise power 6.Dark limitDL 7.Dynamic rangeDR 4

5. Bio-inspired design Assuming an ideal lens, image sensors surpass the human eye in the marked quadrants on both parameters indicated. 5

6. Bio-inspired design Of the 24 image sensors (2000–2010) surveyed, DR and DL tended to be the most limiting factors; these limitations are characteristic features of commercial image sensors. 6

7. Nonlinear response DR SNDR Logarithmic sensor Wide DR Low PSNDR Linear sensor Narrow DR High PSNDR Images © IMS Chips http://www.ims-chips.de/http://www.ims-chips.de/ 7

8. Nonlinear response With linear sensors, photodiode capacitance is first charged at the beginning of each frame, and then discharged by photocurrent during exposure. With logarithmic sensors, response is achieved via a CMOS transistor (T pd ) operating in sub-threshold. Linear sensorLogarithmic sensor 8

9. Nonlinear response Two paths to achieve wide DR and high PSNDR: Improve DR of high-PSNDR linear sensors; Improve SNDR of wide-DR nonlinear sensors. SNDR is affected by two types of noise: Temporal noise, i.e., time-varying noise; Spatial distortion, i.e., fixed pattern noise (FPN). Our team developed new methods for FPN correction, of nonlinear sensors, to the limit of temporal noise. The methods, which are computationally efficient, are suitable for both still-image and video applications. 9

10. Nonlinear response The image shown was taken with logarithmic CMOS active pixel sensor (APS) arrays designed in our lab. Initial calibration of the sensor array is required. Original imageCorrected image 10

11. Digital pixels 11 FPN is corrected to the limit of temporal noise with methods we developed. However, PSNDR of logarithmic CMOS APS arrays remains low because it is limited by PSNR. No logarithmic CMOS APS array has achieved a PSNDR higher than that of the human eye.

12. Digital pixels Linear CMOS APS arrays are integrating designs: Finite-duration integration approximates a first-order low-pass filter (LPF) with a narrow bandwidth (BW); The LPF reduces temporal noise, resulting in high PSNR, which enables high PSNDR and high image quality. Logarithmic CMOS APS arrays are non-integrating: Consequently, each pixel sensor has a wide BW; The wide noise spectrum results in low PSNDR. With CMOS APS arrays, data conversion is done at chip or column level; pixel-level digitization enables noise filtering and protection from further noise. 12

13. Digital pixels We designed and tested logarithmic CMOS digital pixel sensor (DPS) arrays with fully-integrated ΔΣ ADCs. They demonstrated a 43 dB PSNDR at video rates, surpassing the human eye’s PSNDR of 36 dB. 13 Pixel layoutSample image

14. Multiple-tier processes Also, the DPS array’s SR is low because the ΔΣ ADCs each require many transistors; in other words, pixel size is too large for standard optical imaging. 14 DL of the DPS array is comparable to that of standard CMOS APS (and CCD) arrays. But it is two orders of magnitude worse than the human eye’s DL (colour vision).

15. Multiple-tier processes Vertical integration of heterogeneous tiers allows an optimized process to be used with each one. Fabrication of ADC circuits in a nanoscale process facilitates DPS arrays with higher SR. 15 SR depends also on integration technology, which is improving. Photodetector optimization can improve DL.

16. Multiple-tier processes We designed and tested logarithmic vertically- integrated (VI) CMOS APS arrays that were assembled by flip-chip bonding. Designs are composed of CMOS and photodetector dies, which employ hydrogenated amorphous silicon detectors. 16 The VI-CMOS APS array demonstrated a DL that is an order of magnitude better than that of typical CMOS APS (and CCD) sensor arrays.

17. Multiple-tier processes Sensor 25, the CMOS APS array, has wide DR but low PSNDR. Sensor 27, the VI-CMOS APS array, has low DL; it is compatible with Sensor 26, the CMOS DPS array, which has high PSNDR. We expect superior performance with nonlinear digital pixels in multiple-tier processes, i.e., with VI-CMOS DPS arrays. 17

18. Conclusion The approach presented here for image sensor design is inspired by the performance of the corresponding biological system rather than by its structure. Compared to the human eye, DR and DL are the most limiting factors of conventional image sensors. FPN of logarithmic CMOS APS arrays, which easily achieve wide DR, can be corrected effectively. With CMOS DPS arrays, in-pixel ΔΣ ADCs are used to filter temporal noise and achieve high PSNDR. To achieve low DL, and to pursue high SR, multiple-tier processes, or VI-CMOS technology, is investigated. 18

19. Acknowledgments The authors would like to thank: Dr. Kamal Ranaweera; Dr. Jianzeng Xu; Dr. Glen Fitzpatrick; NSERC; Alberta Innovates— Technology Futures; CMC Microsystems; Micralyne. 19