Image denoising using a directional adaptive diffusion filter

Cuifang Zhao; Caicheng Shi; Peikun He

doi:10.1117/12.716728

24 October 2006 Image denoising using a directional adaptive diffusion filter

Cuifang Zhao, Caicheng Shi, Peikun He

Proceedings Volume 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence; 63570D (2006) https://doi.org/10.1117/12.716728
Event: Sixth International Symposium on Instrumentation and Control Technology, 2006, Beijing, China

Abstract

Partial differential equations (PDEs) are well-known due to their good processing results which it can not only smooth the noise but also preserve the edges. But the shortcomings of these processes came to being noticed by people. In some sense, PDE filter is called "cartoon model" as it produces an approximation of the input image, use the same diffusion model and parameters to process noise and signal because it can not differentiate them, therefore, the image is naturally modified toward piecewise constant functions. A new method called a directional adaptive diffusion filter is proposed in the paper, which combines PDE mode with wavelet transform. The undecimated discrete wavelet transform (UDWT) is carried out to get different frequency bands which have obviously directional selectivity and more redundancy details. Experimental results show that the proposed method provides a performance better to preserve textures, small details and global information.

Citation Download Citation

Cuifang Zhao, Caicheng Shi, and Peikun He "Image denoising using a directional adaptive diffusion filter", Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63570D (24 October 2006); https://doi.org/10.1117/12.716728

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