Stability of Efficient Deterministic Compressed Sensing for Images with Chirps and Reed-Muller Sequences

作     者：Somantika Datta Kangyu Ni Prasun Mahanti Svetlana Roudenko 

作者机构：Department of Mathematics George Washington University Washington DC USA Department of Mathematics University of Idaho Moscow USA HRL Laboratories LLC Malibu USA School of Electrical Computer and Energy Engineering Arizona State University Tempe USA 

出 版 物：《Applied Mathematics》 (应用数学（英文）)

年 卷 期：2013年第4卷第1期

页      面：183-196页

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Compressed Sensing Reed-Muller Sequences Chirps Image Reconstruction 

摘      要：We explore the stability of image reconstruction algorithms under deterministic compressed sensing. Recently, we have proposed [1-3] deterministic compressed sensing algorithms for 2D images. These algorithms are suitable when Daubechies wavelets are used as the sparsifying basis. In the initial work, we have shown that the algorithms perform well for images with sparse wavelets coefficients. In this work, we address the question of robustness and stability of the algorithms, specifically, if the image is not sparse and/or if noise is present. We show that our algorithms perform very well in the presence of a certain degree of noise. This is especially important for MRI and other real world applications where some level of noise is always present.