文件名称:Inpainting--on-Wavelet-
- 所属分类:
- 图形图像处理(光照,映射..)
- 资源属性:
- [PDF]
- 上传时间:
- 2012-11-26
- 文件大小:
- 240kb
- 下载次数:
- 0次
- 提 供 者:
- Ank***
- 相关连接:
- 无
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图像修复是图像处理的一个重要问题。这是一个困难的问题,同时填写在地区缺少图像信息的纹理和结构。以损坏的图像inpaint失踪的结构和纹理信息,基于小波分解的图像修补算法提出。首先损坏的图像分解成子图像和纹理结构,利用小波子图像转变。然后,地区结构中缺少的信息的子图像重建曲率驱动扩散(CDD),算法,而在同一区域的纹理子图像填写基于改进的纹理合成的典范 最后,恢复的图像,通过重组,结构和纹理恢复的结果。大量的实验表明,该算法可以快速,高效地恢复在同一时间的结构和纹理信息,视觉效果和峰值信噪比比(PSNR)比同类算法更好。-Image inpainting is an important problem image processing. It is a difficult problem to simultaneously fill-in the
texture and structure in regions of missing image information. In order to inpaint the damaged image with both
missing the structure and texture information, an image inpainting algorithm based on wavelet decomposition is
presented. First the damaged image is decomposed into structure sub-image and texture sub-image using the wavelet
transformation. Then, the sub-image with the region of missing information in the structure is reconstructed by
Curvature-Driven Diffusions (CDD) algorithm, while the same region in the texture sub-image is filled-in with the
improved texture synthesis based on exemplar Finally, the restored image is given by recombining the structure and
texture restored results. A large number of experiments show that the proposed algorithm can quickly and efficiently
restore the structure and texture information at the same time, and the visual eff
texture and structure in regions of missing image information. In order to inpaint the damaged image with both
missing the structure and texture information, an image inpainting algorithm based on wavelet decomposition is
presented. First the damaged image is decomposed into structure sub-image and texture sub-image using the wavelet
transformation. Then, the sub-image with the region of missing information in the structure is reconstructed by
Curvature-Driven Diffusions (CDD) algorithm, while the same region in the texture sub-image is filled-in with the
improved texture synthesis based on exemplar Finally, the restored image is given by recombining the structure and
texture restored results. A large number of experiments show that the proposed algorithm can quickly and efficiently
restore the structure and texture information at the same time, and the visual eff
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