DocumentCode :
1381759
Title :
A CMOS Image Sensor With On-Chip Image Compression Based on Predictive Boundary Adaptation and Memoryless QTD Algorithm
Author :
Chen, Shoushun ; Bermak, Amine ; Wang, Yan
Author_Institution :
Sch. of Electron. & Electr. Eng., Nanyang Technol. Univ., Singapore, Singapore
Volume :
19
Issue :
4
fYear :
2011
fDate :
4/1/2011 12:00:00 AM
Firstpage :
538
Lastpage :
547
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.
Keywords :
CMOS image sensors; VLSI; data compression; differential pulse code modulation; image coding; quantisation (signal); random-access storage; time-domain analysis; CMOS image sensor; DPCM procedure; FBAR procedure; VLSI hardware; adaptive quantization scheme; differential pulse code modulation; fast boundary adaptation rule; image acquisition; image array; image compression processor; image storage; least storage quadrant tree decomposition processing; memoryless QTD algorithm; nondestructive storage capability; on-chip image compression; peak signal-to-noise ratio levels; pixel-level memory; power 17 mW; predictive boundary adaptation; size 0.35 mum; static-RAM device; time domain digital pixel sensor technology; uncompressed illumination data; word length 8 bit; CMOS image sensor; Hilbert Scan; on-chip image compression; quadrant tree decomposition (QTD);
fLanguage :
English
Journal_Title :
Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1063-8210
Type :
jour
DOI :
10.1109/TVLSI.2009.2038388
Filename :
5382495
Link To Document :
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