Adaptive Block-Wise Compressive Image Sensing Based on Visual Perception

Xue ZHANG  Anhong WANG  Bing ZENG  Lei LIU  Zhuo LIU  

IEICE TRANSACTIONS on Information and Systems   Vol.E96-D   No.2   pp.383-386
Publication Date: 2013/02/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E96.D.383
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Processing and Video Processing
compressive sensing,  human visual perception,  adaptive sampling,  DCT,  

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Numerous examples in image processing have demonstrated that human visual perception can be exploited to improve processing performance. This paper presents another showcase in which some visual information is employed to guide adaptive block-wise compressive sensing (ABCS) for image data, i.e., a varying CS-sampling rate is applied on different blocks according to the visual contents in each block. To this end, we propose a visual analysis based on the discrete cosine transform (DCT) coefficients of each block reconstructed at the decoder side. The analysis result is sent back to the CS encoder, stage-by-stage via a feedback channel, so that we can decide which blocks should be further CS-sampled and what is the extra sampling rate. In this way, we can perform multiple passes of reconstruction to improve the quality progressively. Simulation results show that our scheme leads to a significant improvement over the existing ones with a fixed sampling rate.