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Abstract
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Article Information:
Image Denoising of Wavelet based Compressed Images Corrupted by Additive White Gaussian Noise
Shyam Lal and Mahesh Chandra
Corresponding Author: Shyam Lal
Submitted: March 12, 2012
Accepted: April 03, 2012
Published: September 01, 2012 |
Abstract:
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In this study an efficient algorithm is proposed for removal of additive white Gaussian noise from
compressed natural images in wavelet based domain. First, the natural image is compressed by discrete wavelet
transform and then proposed hybrid filter is applied for image denoising of compressed images corrupted by
Additive White Gaussian Noise (AWGN). The proposed hybrid filter (HMCD) is combination of non-linear
fourth order partial differential equation and bivariate shrinkage function. The proposed hybrid filter provides
better results in term of noise suppression with keeping minimum edge blurring as compared to other existing
image denoising techniques for wavelet based compressed images. Simulation and experimental results on
benchmark test images demonstrate that the proposed hybrid filter attains competitive image denoising
performances as compared with other state-of-the-art image denoising algorithms. It is more effective
particularly for the highly corrupted images in wavelet based compressed domain.
Key words: Bivariate shrinkage function, fourth order PDE, hybrid filter, image denoising, natural images, ,
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Cite this Reference:
Shyam Lal and Mahesh Chandra, . Image Denoising of Wavelet based Compressed Images Corrupted by Additive White Gaussian Noise. Research Journal of Applied Sciences, Engineering and Technology, (17): 3108-3118.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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