A CMOS image sensor with on-chip image compression based on predictive boundary adaptation and memoryless QTD algorithm

Authors:
Shoushun Chen;Amine Bermak;Yan Wang
Affiliations:
School of Electronic and Electrical Engineering, Nanyang Technological University, Singapore;Department of Electrical and Computer Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong;Department of Electrical and Computer Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong
Venue:
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Year:
2011

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Abstract

This paper presents the architecture, algorithm, and VLSI hardware of image acquisition, storage, and compression on a single-chip CMOS image sensor. The image array is based on time domain digital pixel sensor technology equipped with nondestructive storage capability using 8-bit Static-RAM device embedded at the pixel level. The pixel-level memory is used to store the uncompressed illumination data during the integration mode as well as the compressed illumination data obtained after the compression stage. An adaptive quantization scheme based on fast boundary adaptation rule (FBAR) and differential pulse code modulation (DPCM) procedure followed by an online, least storage quadrant tree decomposition (QTD) processing is proposed enabling a robust and compact image compression processor. A prototype chip including 64 × 64 pixels, read-out and control circuitry as well as an on-chip compression processor was implemented in 0.35 µm CMOS technology with a silicon area of 3.2 × 3.0 mm2 and an overall power of 17 mW. Simulation and measurements results show compression figures corresponding to 0.6-1 bit-per-pixel (BPP), while maintaining reasonable peak signal-to-noise ratio levels.