Study on Compressed Sensing Recovery Algorithms

Ying Zhu; Yong Xing Jia; Chuan Zhen Rong; Yu Yang

doi:10.4028/www.scientific.net/AMM.433-435.322

Paper Titles

A New Adaptive Image Denoising Method Based on Wavelet Packet Transform and Neighbor Dependency
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An Improved Compressive Sensing Image Fusion Algorithm Based on NSCT Transform
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3D Subtitles Superimposed Technical Overview
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Adjustment Method between Phonological Attributes and Phone Boundaries
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Study on Compressed Sensing Recovery Algorithms
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An Efficient Multi-Hypothesis Temporal Error Concealment Method for H.264
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Research on Image Scene Semantics Recognition System
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Learning Facial Expression Codes with Sparse Auto-Encoder
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Thenar Palmprint Image Denoising Based on Intermediary Filter
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 433-435Study on Compressed Sensing Recovery Algorithms

Study on Compressed Sensing Recovery Algorithms

Abstract:

Abastruct. Compressive sensing is a novel signal sampling theory under the condition that the signalis sparse or compressible.In this case,the small amount of signal values can be reconstructed when signal is sparse or compressible.This paper has reviewed the idea of OMP,GBP and SP,given algorithms and analyzed the experiment results,suggested some improvements.