A new algorithm is proposed for completing the missing parts caused by the removal of foreground or background elements from an image of natural scenery in a visually plausible way. The major contributions of the prop...A new algorithm is proposed for completing the missing parts caused by the removal of foreground or background elements from an image of natural scenery in a visually plausible way. The major contributions of the proposed algorithm are： （1） for most natural images, there is a strong orientation of texture or color distribution. So a method is introduced to compute the main direction of the texture and complete the image by limiting the search to one direction to carry out image completion quite fast; （2） there exists a synthesis ordering for image completion. The searching order of the patches is defined to ensure the regions with more known information and the structures should be completed before filling in other regions; （3） to improve the visual effect of texture synthesis, an adaptive scheme is presented to determine the size of the template window for capturing the features of various scales. A number of examples are given to demonstrate the effectiveness of the proposed algorithm.展开更多
The classical TV (Total Variation) model has been applied to gray texture image denoising and inpainting previously based on the non local operators, but such model can not be directly used to color texture image inpa...The classical TV (Total Variation) model has been applied to gray texture image denoising and inpainting previously based on the non local operators, but such model can not be directly used to color texture image inpainting due to coupling of different image layers in color images. In order to solve the inpainting problem for color texture images effectively, we propose a non local CTV (Color Total Variation) model. Technically, the proposed model is an extension of local TV model for gray images but we take account of the coupling of different layers in color images and make use of concepts of the non-local operators. As the coupling of different layers for color images in the proposed model will in-crease computational complexity, we also design a fast Split Bregman algorithm. Finally, some numerical experiments are conducted to validate the performance of the proposed model and its algorithm.展开更多
A simple and effective image inpainting method is proposed in this paper, which is proved to be suitable for different kinds of target regions with shapes from little scraps to large unseemly objects in a wide range o...A simple and effective image inpainting method is proposed in this paper, which is proved to be suitable for different kinds of target regions with shapes from little scraps to large unseemly objects in a wide range of images. It is an important improvement upon the traditional image inpainting techniques. By introducing a new bijeetive-mapping term into the matching cost function, the artificial repetition problem in the final inpainting image is practically solved. In addition, by adopting an inpainting error map, not only the target pixels are refined gradually during the inpainting process but also the overlapped target patches are combined more seamlessly than previous method. Finally, the inpainting time is dramatically decreased by using a new acceleration method in the matching process.展开更多
We propose a layered image inpainting scheme based on image decomposition. The damaged image is first decomposed into three layers： cartoon, edge, and texture. The cartoon and edge layers are repaired using an adapti...We propose a layered image inpainting scheme based on image decomposition. The damaged image is first decomposed into three layers： cartoon, edge, and texture. The cartoon and edge layers are repaired using an adaptive offset operator that can fill-in damaged image blocks while preserving sharpness of edges. The missing information in the texture layer is generated with a texture synthesis method. By using discrete cosine transform （DCT） in image decomposition and trading between resolution and computation complexity in texture synthesis, the processing time is kept at a reasonable level.展开更多
基于纹理合成的图像修复技术用于修复大面积破损区域,目前此类算法都存在时间复杂度高的缺点。针对纹理算法的匹配技术进行改进,提出了一种基于图像平均灰度值的快速图像匹配算法。该算法在匹配之前预先计算纹理块的平均灰度值以及分割...基于纹理合成的图像修复技术用于修复大面积破损区域,目前此类算法都存在时间复杂度高的缺点。针对纹理算法的匹配技术进行改进,提出了一种基于图像平均灰度值的快速图像匹配算法。该算法在匹配之前预先计算纹理块的平均灰度值以及分割后的纹理块的局部平均灰度值,以取代计算复杂的匹配项SSD(sum of squaredd ifferences);匹配过程只需对平均灰度值进行快速比较,结合阈值控制筛选掉大部分候选纹理块。实验结果表明,该算法在不损害图像修复质量的同时,将纹理修复的效率提高到实时水平。同时在纹理合成和纹理修复中具有普遍的适用性。展开更多
文摘A new algorithm is proposed for completing the missing parts caused by the removal of foreground or background elements from an image of natural scenery in a visually plausible way. The major contributions of the proposed algorithm are： （1） for most natural images, there is a strong orientation of texture or color distribution. So a method is introduced to compute the main direction of the texture and complete the image by limiting the search to one direction to carry out image completion quite fast; （2） there exists a synthesis ordering for image completion. The searching order of the patches is defined to ensure the regions with more known information and the structures should be completed before filling in other regions; （3） to improve the visual effect of texture synthesis, an adaptive scheme is presented to determine the size of the template window for capturing the features of various scales. A number of examples are given to demonstrate the effectiveness of the proposed algorithm.
文摘The classical TV (Total Variation) model has been applied to gray texture image denoising and inpainting previously based on the non local operators, but such model can not be directly used to color texture image inpainting due to coupling of different image layers in color images. In order to solve the inpainting problem for color texture images effectively, we propose a non local CTV (Color Total Variation) model. Technically, the proposed model is an extension of local TV model for gray images but we take account of the coupling of different layers in color images and make use of concepts of the non-local operators. As the coupling of different layers for color images in the proposed model will in-crease computational complexity, we also design a fast Split Bregman algorithm. Finally, some numerical experiments are conducted to validate the performance of the proposed model and its algorithm.
基金Supported by the National Natural Science Foundation of China （No. 60403044, No. 60373070） and partly funded by Microsoft Research Asia： Project 2004-Image-01.
文摘A simple and effective image inpainting method is proposed in this paper, which is proved to be suitable for different kinds of target regions with shapes from little scraps to large unseemly objects in a wide range of images. It is an important improvement upon the traditional image inpainting techniques. By introducing a new bijeetive-mapping term into the matching cost function, the artificial repetition problem in the final inpainting image is practically solved. In addition, by adopting an inpainting error map, not only the target pixels are refined gradually during the inpainting process but also the overlapped target patches are combined more seamlessly than previous method. Finally, the inpainting time is dramatically decreased by using a new acceleration method in the matching process.
基金Project supported by the Shanghai Leading Academic Discipline Project(Grant No.T0102)
文摘We propose a layered image inpainting scheme based on image decomposition. The damaged image is first decomposed into three layers： cartoon, edge, and texture. The cartoon and edge layers are repaired using an adaptive offset operator that can fill-in damaged image blocks while preserving sharpness of edges. The missing information in the texture layer is generated with a texture synthesis method. By using discrete cosine transform （DCT） in image decomposition and trading between resolution and computation complexity in texture synthesis, the processing time is kept at a reasonable level.
文摘基于纹理合成的图像修复技术用于修复大面积破损区域,目前此类算法都存在时间复杂度高的缺点。针对纹理算法的匹配技术进行改进,提出了一种基于图像平均灰度值的快速图像匹配算法。该算法在匹配之前预先计算纹理块的平均灰度值以及分割后的纹理块的局部平均灰度值,以取代计算复杂的匹配项SSD(sum of squaredd ifferences);匹配过程只需对平均灰度值进行快速比较,结合阈值控制筛选掉大部分候选纹理块。实验结果表明,该算法在不损害图像修复质量的同时,将纹理修复的效率提高到实时水平。同时在纹理合成和纹理修复中具有普遍的适用性。
