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

• 作者: Kangyu Ni Prasun Mahanti Somantika Datta Svetlana Roudenko
• 来源期刊: 应用数学(英文)
• 学科: 工学
• 关键词: Compressed SENSING Reed-Muller SEQUENCES Chirps IMAGE RECONSTRUCTION
• 年，卷（期）: 2013,（1）
• 页码范围: 183-196
• 页数: 14页
• 分类号: TP39

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.