Title: Image Reconstruction Based on Compressed Sensing Theory
Abstract: Compression sensing is a new signal acquisition theory, which breaks through the limitation of Nyquist sampling theorem. The sampling frequency of compressed sensing signal is determined by the structure and content of the signal, and the coding and decoding frame of compressed sensing signal is asymmetric. In the compression process, the measurement matrix is used to project the sample values, which is relatively simple to operate. The decoding process involves complex reconstruction operations, and the process is relatively complex. In this paper, a pressure sensing algorithm based on orthogonal matching pursuit is studied. Two advanced algorithms for image reconstruction using OMP are proposed: PartHadamardMtx and BernoulliMtx. Comparing different random matrices, the optimal random matrix is selected adaptively.
Publication Year: 2019
Publication Date: 2019-09-07
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 1
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