Title :
Combined non-local and multi-resolution sparsity prior in image restoration
Author :
Aelterman, Jan ; Goossens, B. ; Hiep Luong ; De Vylder, Jonas ; Pizurica, Aleksandra ; Philips, Wilfried
Author_Institution :
TELIN - IPI - IBBT, Ghent Univ., Ghent, Belgium
fDate :
Sept. 30 2012-Oct. 3 2012
Abstract :
In the field of image denoising, the non-local means (NLMS) filter is a conceptually simple, yet powerful technique. This filter exploits non-local, i.e. spatially repetitive, structure in natural images to estimate noise-free structure. In contrast, a wide variety of image restoration problems have been solved exploiting local smoothness of natural images, e.g. by enforcing sparsity of images when subjected to a multi-resolution transform. In this paper we introduce the prior knowledge of non-local repetitiveness of image structures into a broad multi-resolution image restoration framework. The proposed framework allows the power of the NLMS filter, supplemented by multi-resolution sparsity, to be extended for a wide variety of image restoration problems, such as demosaicing, deconvolution, reconstruction from insufficient measurements,... in a conceptually simple way.
Keywords :
filtering theory; image denoising; image resolution; image restoration; NLMS filter; image denoising; image restoration; multiresolution sparsity; noise-free structure; non-local means filter; nonlocal sparsity; Image denoising; Image resolution; Image restoration; Noise; Noise reduction; Signal processing algorithms; Transforms; Non-local means; denoisaicing; self similarity; shearlet; sparsity;
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2012.6467543