Adaptive-quantization digital image sensor for low-power image compression

Chen Shoushun, Amine Bermak, Wang Yan, Dominique Martinez

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

The recent emergence of new applications in the area of wireless video sensor network and ultra-low-power biomedical applications (such as the wireless camera pill) have created new design challenges and frontiers requiring extensive research work. In such applications, it is often required to capture a large amount of data and process them in real time while the hardware is constrained to take very little physical space and to consume very little power. This is only possible using custom single-chip solutions integrating image sensor and hardware-friendly image compression algorithms. This paper proposes an adaptive quantization scheme based on boundary adaptation procedure followed by an online quadrant tree decomposition processing enabling low power and yet robust and compact image compression processor integrated together with a digital CMOS image sensor. The image sensor chip has been implemented using 0.35-μm CMOS technology and operates at 3.3 V. Simulation and experimental results show compression figures corresponding to 0.6-0.8 bit per pixel, while maintaining reasonable peak signal-to-noise ratio levels and very low operating power consumption. In addition, the proposed compression processor is expected to benefit significantly from higher resolution and Megapixels CMOS imaging technology.

Original languageEnglish
Pages (from-to)13-25
Number of pages13
JournalIEEE Transactions on Circuits and Systems I: Regular Papers
Volume54
Issue number1
DOIs
Publication statusPublished - Jan 2007
Externally publishedYes

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Quantization (signal)
Image compression
Image sensors
Hardware
Sensor networks
Signal to noise ratio
Electric power utilization
Pixels
Cameras
Decomposition
Imaging techniques
Processing

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Adaptive-quantization digital image sensor for low-power image compression. / Shoushun, Chen; Bermak, Amine; Yan, Wang; Martinez, Dominique.

In: IEEE Transactions on Circuits and Systems I: Regular Papers, Vol. 54, No. 1, 01.2007, p. 13-25.

Research output: Contribution to journalArticle

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