Intelligent & Adaptive Image Denoising Based on Wavelets with Shrinkage Rule

Arjunan, Vijaya R and Kumar, Vijaya V (2012) Intelligent & Adaptive Image Denoising Based on Wavelets with Shrinkage Rule. International Journal of Information & Computation Technology, 2 (2). pp. 89-101. ISSN 0974-2239

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Real time image processing should have high quality results at lesser computational time. A spatial image denoising method using 2D discrete Wavelet transform (2D DWT) and Stationary wavelet transform (SWT) is presented in this paper for high quality image results. DWT gives high quality output at low levels of noise at relatively lesser time consumption where as it suffers from translation invariance. SWT overcomes translational invariance by removing the up samplers and down samplers and gives better image quality but consumes more computational time. Considering the advantages of both SWT and DWT, an attempt is made to propose an adaptive and intelligent denoising system which is based on both these wavelet transform methods. The operational schema involves three distinct approaches. The first approach is a buffer unit for approximately clean image. The second approach is based on SWT, and the effects of noise are minimized by soft thresholding at high frequency

Item Type: Article
Additional Information: International Journal of Information & Computation Technology.
Uncontrolled Keywords: 2D DWT, SWT, PSNR, Image quality, Interpolation, Soft threshold
Subjects: Engineering > MIT Manipal > Computer Science and Engineering
Depositing User: MIT Library
Date Deposited: 21 Mar 2013 10:29
Last Modified: 21 Mar 2013 10:29

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