首页> 外文会议>Intelligent Multimedia, Video and Speech Processing, 2004. Proceedings of 2004 International Symposium on >Blocking artifacts reduction for DCT-based image compression using neurofuzzy driven anisotropic diffusion
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Blocking artifacts reduction for DCT-based image compression using neurofuzzy driven anisotropic diffusion

机译:使用神经模糊驱动的各向异性扩散进行基于DCT的图像压缩的块状伪影减少

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In this paper, we propose a new deblocking method for DCT-based compressed images using anisotropic diffusion. An adaptive anisotropic coefficient, derived from a neuro-fuzzy network, is introduced. The optimal diffusion parameters are estimated using a stochastic optimization technique, which ensures that heavy diffusion performs across the block boundaries and in flat regions while image edges are well preserved. Experimental results have shown that the proposed adaptive diffusion method can significantly suppress coding artifacts and improve the visual quality of the compressed image.
机译:在本文中,我们提出了一种利用各向异性扩散的基于DCT的压缩图像的新脱块方法。介绍了来自神经模糊网络的自适应各向异性系数。使用随机优化技术估计最佳扩散参数,其确保重大扩散在块边界和平坦区域中进行,而图像边缘保持良好。实验结果表明,所提出的自适应扩散方法可以显着抑制编码伪像,提高压缩图像的视觉质量。

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