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Communication Dans Un Congrès Année : 2016

Compressive imaging using approximate message passing and a Cauchy prior in the wavelet domain

Résumé

Approximate Message Passing (AMP) is an iterative reconstruction algorithm that performs signal denoising within a compressive sensing framework. We propose the use of heavy tailed distribution based image denoising, specifically using a Cauchy prior based Maximum A-Posteriori (MAP) estimate within a wavelet based AMP compressive sensing structure. The use of this MAP denoising algorithm provides extremely fast convergence for image based compressive sensing. The proposed method converges approximately twice as fast as the compared AMP methods whilst providing superior final MSE results over a range of measurement rates.
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Dates et versions

hal-01523670 , version 1 (16-05-2017)

Identifiants

  • HAL Id : hal-01523670 , version 1
  • OATAO : 16992

Citer

Paul Hill, Jong-Hoon Kim, Adrian Basarab, Denis Kouamé, David Bull, et al.. Compressive imaging using approximate message passing and a Cauchy prior in the wavelet domain. IEEE International Conference on Image Processing (ICIP 2016), Sep 2016, Phoenix, Arizona, United States. pp. 2514-2518. ⟨hal-01523670⟩
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