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Adaptive Directional Lifting-based Wavelet Transform for Image Denoising and Its Implementation

Author: JiaoHengHao
Tutor: XieXueMei
School: Xi'an University of Electronic Science and Technology
Course: Signal and Information Processing
Keywords: Adaptive Directional Lifting Denoising Wavelet Transform Threshold
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 299
Quote: 3
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Abstract


The digital image acquisition and transmission process tend to be affected by noise pollution , how to effectively eliminate noise is an important topic in the image processing . In 1994 , Donoho et al proposed a wavelet thresholding denoising methods , it transforms the image to the wavelet coefficients of the image in the wavelet domain threshold atrophy processing this denoising method has been widely used because of simple and effective . Traditional two-dimensional discrete wavelet transform is not conducive to the expression of the image texture and edge direction information , the details of the image is easily lost when denoising , causing fuzzy image texture and edge . 2007 , Ding et al proposed a separable adaptive directional enhance the wavelet ( ADL ) , it can detect the direction of the texture of the image on the fractional accuracy , and to enhance the direction of the image along the direction of the texture of the image wavelet transform , so that as much as possible to reduce the energy of high-frequency sub-band image decomposition . ADL was originally used in image compression and have been successful. In this article, we transplanted it to the field of image threshold denoising using its Adaptive Directional Lifting to maintain an image texture information . Meanwhile, ADL improvement, AOL the ( adaptive omnidirectional BY LIFTING ) , compared to the ADL ± 4 5 ° direction Search , AOL was able to search for images in the image of 0 ° ° 360 ° strongest correlation direction , this can be a more accurate approximation of the texture of the image , image texture area better denoising results . AOL is separable wavelet transform , the structure is simple, because lifting transform and its inverse transform easily accessible , conducive to hardware implementation . The experiments show that the method denoised image texture regions regardless of PSNR value or subjective visual effects are superior to traditional two-dimensional discrete wavelet transform .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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