Block Compressed Sensing Based on Image Complexity

Abstract:

Compressed sensing (CS) is a new Compressed sensing (CS) is a new technique for simultaneous data sampling and compression. Inspired by recent theoretical advances in compressive sensing, we propose a new CS algorithm which takes the image complexity into consideration. Image will be divided into small blocks, and then acquisition is conducted in a block-by-block manner. Each block has independent measurement and recovery process. The extraordinary thought proposed is that we sufficiently take advantage of image characteristics in measurement process, which make our measurement more effective and efficient. Experimental results tell that our algorithm has better recovery performance than traditional method, and its calculation amount has greatly reduced.

• Periodical: Applied Mechanics and Materials (Volumes 157-158)
• Pages: 1287-1292
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.157-158.1287
• Online since: February 2012
• Authors: Yu Ming Cao, Yan Feng, Ying Biao Jia, Chang Sheng Dou
• Keywords: Compressed Sensing, Image Complexity, Total-Variation (TV)

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