Inpainting intergrate with decomposition for image compression

Wu Di, Ren Li, Shuang Wu
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引用次数: 1

Abstract

In this paper, we propose an image compression framework that integrates image decomposition technique with image inpainting to exploit visual redundancy in color images. An original image is first decomposed into geometry and texture using nonlinear filter decomposition model. Then, the geometry and texture image are compressed with edge-based inpainting and the standard JPEG respectively. At the decoder side, the decoded texture image adds to geometry image which is decoded using structure propagation and texture synthesis. In this scheme, we study different decomposition models and choose the best decomposition model to get pure texture image. Moreover, robustness of texture image is fully taken advantage. Based on that, more regions can be dropped at the encoder side without sacrificing the image quality. Experimental results show that our method significantly outperforms standard JPEG and image compression with edge-based inpainting.
图像绘制与图像压缩分解相结合
在本文中,我们提出了一个图像压缩框架,该框架将图像分解技术与图像绘制技术相结合,以利用彩色图像中的视觉冗余。首先利用非线性滤波分解模型对原始图像进行几何分解和纹理分解。然后,分别使用基于边缘的图像填充和标准JPEG压缩几何图像和纹理图像。在解码器端,将解码后的纹理图像加入到几何图像中,利用结构传播和纹理合成对几何图像进行解码。在该方案中,我们研究了不同的分解模型,并选择最佳的分解模型来获得纯纹理图像。并且充分利用了纹理图像的鲁棒性。在此基础上,可以在不牺牲图像质量的情况下在编码器侧丢弃更多的区域。实验结果表明,该方法明显优于标准JPEG和基于边缘的图像填充压缩。
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