NDLI: Image denoising using multiple compressive reconstructed images

Content Provider	IEEE Xplore Digital Library
Author	Iqbal, M. Jie Chen
Copyright Year	2011
Description	Author affiliation: School of Electronics and Information Engineering, Beihang University, Beijing - 100191, China (Iqbal, M.; Jie Chen)
Abstract	A novel image denoising technique is proposed using compressive reconstruction framework. Multiple subsets of pixels with partial overlap are selected from noisy image. The subsets of pixels are selected in such a way that every subset will have at least 20% different pixels compared to any other subset. Each subset of pixels is considered as vector of compressive samples from noisy image and a complete image is reconstructed in wavelet domain using compressive sensing reconstruction algorithm. The multiple images obtained from these subsets are merged using statistical techniques to obtain clean image. The proposed technique is tested on several images with different noise level and it was observed that proposed technique produced better denoising results compared to other denoising techniques using wavelets representation of noisy image.
Starting Page	172
Ending Page	176
File Size	1330880
Page Count	5
File Format	PDF
ISBN	9781424493043
e-ISBN	9781424493067
DOI	10.1109/CISP.2011.6099982
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	PSNR Image coding Noise reduction Reconstruction algorithms Noise measurement Image reconstruction Image denoising
Content Type	Text
Resource Type	Article

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