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An adaptive edge-preserving image denoising technique using patch-based weighted-SVD filtering in wavelet domain

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Abstract

Image denoising has always been one of the standard problems in image processing and computer vision. It is always recommendable for a denoising method to preserve important image features, such as edges, corners, etc., during its execution. Image denoising methods based on wavelet transforms have been shown their excellence in providing an efficient edge-preserving image denoising, because they provide a suitable basis for separating noisy signal from the image signal. This paper presents a novel edge-preserving image denoising technique based on wavelet transforms. The wavelet domain representation of the noisy image is obtained through its multi-level decomposition into wavelet coefficients by applying a discrete wavelet transform. A patch-based weighted-SVD filtering technique is used to effectively reduce noise while preserving important features of the original image. Experimental results, compared to other approaches, demonstrate that the proposed method achieves very impressive gain in denoising performance.

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Authors and Affiliations

  1. Jaypee University of Engineering and Technology, Raghogarh, Guna, MP, 473226, India

    Paras Jain & Vipin Tyagi

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  1. Paras Jain
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  2. Vipin Tyagi
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Correspondence to Vipin Tyagi.

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Jain, P., Tyagi, V. An adaptive edge-preserving image denoising technique using patch-based weighted-SVD filtering in wavelet domain. Multimed Tools Appl 76, 1659–1679 (2017). https://doi.org/10.1007/s11042-015-3154-8

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  • DOI: https://doi.org/10.1007/s11042-015-3154-8

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