DocumentCode
134660
Title
Targeted L1L2: Naturalness-constrained image recovery from random projections
Author
Freeman, Greg J. ; Caramanis, Constantine ; Bovik, Alan C.
Author_Institution
Electr. & Comput. Eng., Univ. of Texas at Austin, Austin, TX, USA
fYear
2014
fDate
6-8 April 2014
Firstpage
97
Lastpage
100
Abstract
We devise an elastic net convex program that generates natural-looking compressive sensed images by mimicking features indicative of good quality images. We use the shape parameter of divisively normalized wavelet coefficients to iteratively solve a convex program and target the distribution of each wavelet band. Using this method we are able to create better quality images than other methods as gauged by perceptually relevant quality indices (SSIM).
Keywords
compressed sensing; convex programming; L1L2; SSIM; elastic net convex program; good quality images; natural-looking compressive sensed images; naturalness-constrained image recovery; normalized wavelet coefficients; perceptually relevant quality indices; random projections; Compressed sensing; Image coding; Image quality; Image reconstruction; Matching pursuit algorithms; Shape; Wavelet domain; Compressed sensing; image quality;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Analysis and Interpretation (SSIAI), 2014 IEEE Southwest Symposium on
Conference_Location
San Diego, CA
Type
conf
DOI
10.1109/SSIAI.2014.6806038
Filename
6806038
Link To Document