Paper Info
Title
Restoration for weakly blurred and strongly noisy images
Abstract
In this paper we present an adaptive sharpening algorithm for restoration of an image which has been corrupted by mild blur, and strong noise. Most existing adaptive sharpening algorithms can not handle strong noise well due to the intrinsic contradiction between sharpening and de-noising. To solve this problem we propose an algorithm that is capable of capturing local image structure and sharpness, and adjusting sharpening accordingly so that it effectively combines denoising and sharpening together without either noise magnification or over-sharpening artifacts. It also uses structure information from the luminance channel to remove artifacts in the chrominance channels. Experiments illustrate that compared with other sharpening approaches, our method can produce state of the art results under practical imaging conditions.
Year
DOI
Venue
2011
10.1109/WACV.2011.5711490
WACV
Keywords
Field
DocType
luminance channel,structure information,noise magnification,strong noise,existing adaptive,mild blur,intrinsic contradiction,chrominance channel,local image structure,art result,noisy image,pixel,image restoration,noise reduction,noise measurement,kernel,edge detection,noise
Sharpening,Kernel (linear algebra),Noise reduction,Computer vision,Noise measurement,Pattern recognition,Computer science,Chrominance,Artificial intelligence,Pixel,Image restoration,Luminance
Conference
Citations 
PageRank 
References 
4
0.39
13
Authors
2
Name
Order
Citations
PageRank
Xiang Zhu126410.86
Peyman Milanfar23284155.61