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Improved Hidden Markov Tree Model and its Application in Image Denoising

机译:改进了隐马尔可夫树模型及其在图像去噪中的应用

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Wavelet coefficients of natural images have significant dependencies. HMT model only capture the interscale dependencies. In this paper we propose an improved HMT model, which simply model intrascale dependencies as multivariate Gaussian distribution. This model is also applied to image denoising. Experimental results show that it can provide better performance than HMT model.
机译:自然图像的小波系数具有显着的依赖性。 HMT模型仅捕获IntersCale依赖项。在本文中,我们提出了一种改进的HMT模型,其简单地模拟了IntraStAscale依赖性作为多变量高斯分布。该模型也应用于图像去噪。实验结果表明它可以提供比HMT模型更好的性能。

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