A new patch-based texture synthesis method is presented in this paper. By the method, a set of patches that can be matched with a sampled patch for growing textures effectively, called the matching compatibility betwe...A new patch-based texture synthesis method is presented in this paper. By the method, a set of patches that can be matched with a sampled patch for growing textures effectively, called the matching compatibility between patches, is generated first for each patch, and the set is further optimized by culling the patches that may cause synthesis conflicts. In this way, similarity measurement calculation for selecting suitable patches in texture synthesis can be greatly saved, and synthesis conflicts between neighbouring patches are substantially reduced. Furthermore, retrace computation is integrated in the synthesis process to improve the texture quality. As a result, the new method can produce high quality textures as texture optimization, the best method to date for producing good textures, and run in a time complexity linear to the size of the output texture. Experimental results show that the new method can interactively generate a large texture in 1024 × 1024 pixels, which is very difficult to achieve by existing methods.展开更多
Because texture images cannot be directly processed by the gray level information of individual pixel,we propose a new texture descriptor which reflects the intensity distribution of the patch centered at each pixel.T...Because texture images cannot be directly processed by the gray level information of individual pixel,we propose a new texture descriptor which reflects the intensity distribution of the patch centered at each pixel.Then the general multiphase image segmentation model of Potts model is extended for texture segmentation by adding the region information of the texture descriptor.A fast numerical scheme based on the split Bregman method is designed to speed up the computational process.The algorithm is efficient,and both the texture descriptor and the characteristic functions can be implemented easily.Experiments using synthetic texture images,real natural scene images and synthetic aperture radar images are presented to give qualitative comparisons between our method and other state-of-the-art techniques.The results show that our method can accurately segment object regions and is competitive compared with other methods especially in segmenting natural images.展开更多
基金Supported by the National Basic Research Program of China (Grant No. 2009CB320802)the National Natural Science Foundation of China (Grant Nos. 60773026, 60833007)+1 种基金the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z306,2008AA01Z301)the Research Grant of University of Macao
文摘A new patch-based texture synthesis method is presented in this paper. By the method, a set of patches that can be matched with a sampled patch for growing textures effectively, called the matching compatibility between patches, is generated first for each patch, and the set is further optimized by culling the patches that may cause synthesis conflicts. In this way, similarity measurement calculation for selecting suitable patches in texture synthesis can be greatly saved, and synthesis conflicts between neighbouring patches are substantially reduced. Furthermore, retrace computation is integrated in the synthesis process to improve the texture quality. As a result, the new method can produce high quality textures as texture optimization, the best method to date for producing good textures, and run in a time complexity linear to the size of the output texture. Experimental results show that the new method can interactively generate a large texture in 1024 × 1024 pixels, which is very difficult to achieve by existing methods.
基金supported by the National Natural Science Foundation of China(No.61170106)
文摘Because texture images cannot be directly processed by the gray level information of individual pixel,we propose a new texture descriptor which reflects the intensity distribution of the patch centered at each pixel.Then the general multiphase image segmentation model of Potts model is extended for texture segmentation by adding the region information of the texture descriptor.A fast numerical scheme based on the split Bregman method is designed to speed up the computational process.The algorithm is efficient,and both the texture descriptor and the characteristic functions can be implemented easily.Experiments using synthetic texture images,real natural scene images and synthetic aperture radar images are presented to give qualitative comparisons between our method and other state-of-the-art techniques.The results show that our method can accurately segment object regions and is competitive compared with other methods especially in segmenting natural images.
