Self‐guided filter for image denoising

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Abstract
The guided filter has been acknowledged as an exceptional edge‐preserving filter whose output is a locally linear transform of the guidance image. However, the traditional guided filter heavily relies on the guidance image and fails to achieve the desired result when performing image denoising without a clear guidance image. In this study, to address this limitation, the authors propose a simple yet effective guided filter variant for the single image noise removing. They further show that the proposed denoising strategy can be easily realised by using the iterative framework. Moreover, the weak textured patches based image noise estimation is utilised to generate a clear intermediate image which makes the proposed method highly adaptable to the local noise level. Experimental results demonstrate that their proposed algorithm can compete with the state‐of‐the‐art local denoising methods in edge‐preserving.
Funding Information
  • Natural Science Foundation of Jiangsu Province (SBK2020042047)

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