JOURNAL ARTICLE

Adaptive Perceptual Block Compressive Sensing for Image Compression

Jin XuYuansong QiaoZhizhong Fu

Year: 2016 Journal:   IEICE Transactions on Information and Systems Vol: E99.D (6)Pages: 1702-1706   Publisher: Institute of Electronics, Information and Communication Engineers

Abstract

Because the perceptual compressive sensing framework can achieve a much better performance than the legacy compressive sensing framework, it is very promising for the compressive sensing based image compression system. In this paper, we propose an innovative adaptive perceptual block compressive sensing scheme. Firstly, a new block-based statistical metric which can more appropriately measure each block's sparsity and perceptual sensibility is devised. Then, the approximated theoretical minimum measurement number for each block is derived from the new block-based metric and used as weight for adaptive measurements allocation. The obtained experimental results show that our scheme can significantly enhance both objective and subjective performance of a perceptual compressive sensing framework.

Keywords:
Compressed sensing Computer science Block (permutation group theory) Metric (unit) Compression (physics) Perception Image compression Artificial intelligence Computer vision Measure (data warehouse) Algorithm Image (mathematics) Image processing Mathematics Data mining Materials science Engineering

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9
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0.90
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12
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0.75
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Citation History

Topics

Sparse and Compressive Sensing Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Blind Source Separation Techniques
Physical Sciences →  Computer Science →  Signal Processing
Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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