Design of Scalable Hardware-Efficient Compressive Sensing Image Sensors

Leitner, Stefan; Wang, Haibo; Tragoudas, Spyros

doi:10.1109/jsen.2017.2766040

Cited by 7 publications

(2 citation statements)

References 28 publications

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“…In order to avoid complex optical systems, some on-chip compressed sensing schemes have been proposed in conventional imaging sensors, which could realize efficient data reading and reduced data bandwidth. Conventional CMOS image sensor converts light intensity into electrical signals for each pixel individually, while CS CMOS image sensors only sample a small set of random pixel summations [15][16][17][18][19][20][21], which can reduce the size of output data, analog to digital conversion (ADC) operations and the sensor power consumption.…”

Section: Related Workmentioning

confidence: 99%

“…Since 2006, the theory of compressed sensing (CS) [12][13][14] has been proposed for efficient data sampling and high-fidelity sparse recovery. Implementing the idea of CS on the CMOS (complementary metal-oxide-semiconductor) sensor chip has been recently proposed [15][16][17][18][19][20][21] and shows promising data throughput reduction on conventional sensing techniques.…”

Section: Introductionmentioning

confidence: 99%

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On-Chip Compressive Sensing with a Single-Photon Avalanche Diode Array

Qiu

Wang

Kong

et al. 2023

Sensors

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Single-photon avalanche diodes (SPADs) are novel image sensors that record photons at extremely high sensitivity. To reduce both the required sensor area for readout circuits and the data throughput for SPAD array, in this paper, we propose a snapshot compressive sensing single-photon avalanche diode (CS-SPAD) sensor which can realize on-chip snapshot-type spatial compressive imaging in a compact form. Taking advantage of the digital counting nature of SPAD sensing, we propose to design the circuit connection between the sensing unit and the readout electronics for compressive sensing. To process the compressively sensed data, we propose a convolution neural-network-based algorithm dubbed CSSPAD-Net which could realize both high-fidelity scene reconstruction and classification. To demonstrate our method, we design and fabricate a CS-SPAD sensor chip, build a prototype imaging system, and demonstrate the proposed on-chip snapshot compressive sensing method on the MINIST dataset and real handwritten digital images, with both qualitative and quantitative results.

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