Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/92047
Title: Adaptive-quantization digital image sensor for low-power image compression
Authors: Chen, Shoushun
Amine, Bermak
Wang, Yan
Dominique, Martinez
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems
Issue Date: 2007
Source: Chen, S., Amine, B., Wang, Y., & Dominique, M. (2007). Adaptive-quantization digital image sensor for low-power image compression. IEEE Transactions on Circuits and Systems Part 1 Regular Papers. 54(1), 13-25.
Series/Report no.: IEEE transactions on circuits and systems part 1 regular papers
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- m 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.
URI: https://hdl.handle.net/10356/92047
http://hdl.handle.net/10220/6330
ISSN: 1549-8328
DOI: http://dx.doi.org/10.1109/TCSI.2006.887460
Rights: © 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. http://www.ieee.org/portal/site This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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