Abstract：Perona-Malik (P-M) model is a classical anisotropic diffusion denoising model, but it is not able to preserve the important details effectively such as the texture of the image. To address this problem, an improved P-M model based on local entropy is proposed. The diffusion coefficient of the model not only depends on the image gradient, but also depends on the local region information described by local entropy. The experimental results show that the proposed model removes noises effectively, preserves the boundaries better, and maintains important details of the image well.
赵德，何传江，陈强. 结合局部熵的各向异性扩散模型[J]. 模式识别与人工智能, 2012, 25(4): 642-647.
ZHAO De, HE Chuan-Jiang, CHEN Qiang. Anisotropic Diffusion Model Combined with Local Entropy. , 2012, 25(4): 642-647.
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