Block-Based Transform-Domain Measurement Coding for Compressive Sensing of Images 


Vol. 39,  No. 12, pp. 746-755, Dec.  2014


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  Abstract

Compressive sensing (CS) has drawn much interest as a new sampling technique that enables signals to be sampled at a much lower than the Nyquist rate. By noting that the block-based compressive sensing can still keep spatial correlation in measurement domain, in this paper, we propose a novel encoding technique for measurement data obtained in the block-based CS of natural image. We apply discrete wavelet transform (DWT) to decorrelate CS measurements and then assign a proper quantization scheme to those DWT coefficients. Thus, redundancy of CS measurements and bitrate of system are reduced remarkably. Experimental results show improvements in rate-distortion performance by the proposed method against two existing methods of scalar quantization (SQ) and differential pulse-code modulation (DPCM). In the best case, the proposed method gains up to 4 dB, 0.9 dB, and 2.5 dB compared with the Block-based CS-Smoothed Projected Landweber plus SQ, Block-based CS-Smoothed Projected Landweber plus DPCM, and Multihypothesis Block-based CS-Smoothed Projected Landweber plus DPCM, respectively.

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  Cite this article

[IEEE Style]

Q. H. Nguyen, V. A. Nguyen, C. V. Trinh, K. Q. Dinh, Y. Park, B. Jeon, "Block-Based Transform-Domain Measurement Coding for Compressive Sensing of Images," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 12, pp. 746-755, 2014. DOI: .

[ACM Style]

Quang Hong Nguyen, Viet Anh Nguyen, Chien Van Trinh, Khanh Quoc Dinh, Younghyeon Park, and Byeungwoo Jeon. 2014. Block-Based Transform-Domain Measurement Coding for Compressive Sensing of Images. The Journal of Korean Institute of Communications and Information Sciences, 39, 12, (2014), 746-755. DOI: .

[KICS Style]

Quang Hong Nguyen, Viet Anh Nguyen, Chien Van Trinh, Khanh Quoc Dinh, Younghyeon Park, Byeungwoo Jeon, "Block-Based Transform-Domain Measurement Coding for Compressive Sensing of Images," The Journal of Korean Institute of Communications and Information Sciences, vol. 39, no. 12, pp. 746-755, 12. 2014.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880