NDLI: Universal and low-complexity quantizer design for compressive sensing image coding

Content Provider	IEEE Xplore Digital Library
Author	Xiangwei Li Xuguang Lan Meng Yang Jianru Xue Nanning Zheng
Copyright Year	2013
Description	Author affiliation: Inst. of Artificial Intell. & Robot., Jiaotong Univ., Xi'an, China (Xiangwei Li; Xuguang Lan; Meng Yang; Jianru Xue; Nanning Zheng)
Abstract	Compressive sensing imaging (CSI) is a new framework for image coding, which enables acquiring and compressing a scene simultaneously. The CS encoder shifts the bulk of the system complexity to the decoder efficiently. Ideally, implementation of CSI provides lossless compression in image coding. In this paper, we consider the lossy compression of the CS measurements in CSI system. We design a universal quantizer for the CS measurements of any input image. The proposed method firstly establishes a universal probability model for the CS measurements in advance, without knowing any information of the input image. Then a fast quantizer is designed based on this established model. Simulation result demonstrates that the proposed method has nearly optimal rate-distortion (R~D) performance, meanwhile, maintains a very low computational complexity at the CS encoder.
Starting Page	1
Ending Page	5
File Size	549483
Page Count	5
File Format	PDF
e-ISBN	9781479902903
DOI	10.1109/VCIP.2013.6706403
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-17
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Quantization (signal) Image coding Computational modeling Quantization Gaussian distribution Compressive sensing imaging Decoding Computational complexity Compressed sensing
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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