Back to articles
Articles
Volume: 28 | Article ID: art00025
Image
Exploiting Structure and Variable Dependency Modeling in Block-based Compressed Sensing Image Reconstruction in the Presence of Non-linear Mixtures
  DOI :  10.2352/ISSN.2470-1173.2016.19.COIMG-173  Published OnlineFebruary 2016
Abstract

With the introduction of compressed sensing (CS) theory, investigation into exploiting sparseness and optimizing compressive sensing performance has ensued. Compressed sensing is highly applicable to images, which naturally have sparse representations. Improvements in the area of image denoising have resulted from the combination of highly-directional transforms with shrinkage and thresholding techniques along with imposition of a model to account for statistical properties of images. Using this approach, statistical modeling of dependencies in the transform domain is incorporated into high-performance and efficient state-of-the-art CS image reconstruction algorithms with highly-directional transforms incorporating redundancy and bivariate shrinkage and thresholding to further refine image reconstruction performance improvements. Additionally, hierarchical structural dependency modeling is incorporated to account for parent–child coefficient relationships. These techniques exploit hierarchical structure and multiscale subbands of frequencies and orientation, exploiting dependencies across and within scales. Additionally, these techniques are incorporated with minimal additional CPU execution time into block-based CS (BCS) algorithms, which are known for their efficient and fast computation time. Experimental results show increased refinements of image reconstruction performance over current state-of-the-art image reconstruction algorithms, particularly at the higher CS ratios (lower sampling rates) of interest in compressed sensing. © 2015 Society for Imaging Science and Technology. [DOI: 10.2352/J.ImagingSci.Technol.2015.59.6.060406]

Subject Areas :
Views 3
Downloads 0
 articleview.views 3
 articleview.downloads 0
  Cite this article 

Lynn M Keuthan, Robert J Harrington, Jefferson M Willey, "Exploiting Structure and Variable Dependency Modeling in Block-based Compressed Sensing Image Reconstruction in the Presence of Non-linear Mixturesin Proc. IS&T Int’l. Symp. on Electronic Imaging: Computational Imaging XIV,  2016,  https://doi.org/10.2352/ISSN.2470-1173.2016.19.COIMG-173

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2016
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151 USA