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Journal of Electronic Imaging

Low bit rates image compression via adaptive block downsampling and super resolution
Author(s): Honggang Chen; Xiaohai He; Minglang Ma; Linbo Qing; Qizhi Teng
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Paper Abstract

A low bit rates image compression framework based on adaptive block downsampling and super resolution (SR) was presented. At the encoder side, the downsampling mode and quantization mode of each 16 × 16 macroblock are determined adaptively using the ratio distortion optimization method, then the downsampled macroblocks are compressed by the standard JPEG. At the decoder side, the sparse representation-based SR algorithm is applied to recover full resolution macroblocks from decoded blocks. The experimental results show that the proposed framework outperforms the standard JPEG and the state-of-the-art downsampling-based compression methods in terms of both subjective and objective comparisons. Specifically, the peak signal-to-noise ratio gain of the proposed framework over JPEG reaches up to 2 to 4 dB at low bit rates, and the critical bit rate to JPEG is raised to about 2.3 bits per pixel. Moreover, the proposed framework can be extended to other block-based compression schemes.

Paper Details

Date Published: 7 January 2016
PDF: 10 pages
J. Electron. Imaging. 25(1) 013004 doi: 10.1117/1.JEI.25.1.013004
Published in: Journal of Electronic Imaging Volume 25, Issue 1
Show Author Affiliations
Honggang Chen, Sichuan Univ. (China)
Xiaohai He, Sichuan Univ. (China)
Minglang Ma, Sichuan Univ. (China)
Linbo Qing, Sichuan Univ. (China)
Qizhi Teng, Sichuan Univ. (China)

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