The priority of the filled patch play a key role in the exemplar-based image inpainting, and it should be determined firstly to optimize the process of image inpainting. A modified image inpainting algorithm is propos...The priority of the filled patch play a key role in the exemplar-based image inpainting, and it should be determined firstly to optimize the process of image inpainting. A modified image inpainting algorithm is proposed by weighted-priority based on the Criminisi algorithm. The improved algorithm demonstrates better relationship between the data term and the confidence term for the optimization of the priority than the classical Criminisi algorithm. By comparing the effect of the inpainted images with different structure, conclusion can be drawn that the optimal priority should be chosen properly for different images with different structures.展开更多
This paper proposes a novel exemplar- based method for reducing noise in computed tomography （CT） images. In the proposed method, denoising is performed on each block with the help of a given database of standard im...This paper proposes a novel exemplar- based method for reducing noise in computed tomography （CT） images. In the proposed method, denoising is performed on each block with the help of a given database of standard image blocks. For each noisy block, its denoised version is the best sparse positive linear combination of the blocks in the database. We formulate the problem as a constrained optimization problem such that the solution is the denoised block. Experimental results demonstrate the good performance of the proposed method over current state-of-the-art denoising methods, in terms of both objective and subjective evaluations.展开更多
In the exemplar-based image inpainting approach,there are usually two major problems:the unreasonable calculation of priority and only considering the color features in the patch lookup strategy.In this paper,we propo...In the exemplar-based image inpainting approach,there are usually two major problems:the unreasonable calculation of priority and only considering the color features in the patch lookup strategy.In this paper,we propose an image inpainting approach based on the structural tensor edge intensity model.First,we use the progressive scanning inpainting method to avoid the image filling order being affected by the priority function.Then,we use the edge intensity model to build the patches similarity function for correctly identifying the local image structure.Finally,the balance operator is used to restrict the excessive propagation of structural information to ensure the correct structural reconstruction.The experimental results show that the our approach is comparable and even superior to some state-of-the-art inpainting algorithms.展开更多
基金Supported by the National Natural Science Foundation of China (No. 60972106)Postdoctoral Science Foundation (No. 20090450750)the Science Foundation of Tianjin(No. 11JCYBJC00900)
文摘The priority of the filled patch play a key role in the exemplar-based image inpainting, and it should be determined firstly to optimize the process of image inpainting. A modified image inpainting algorithm is proposed by weighted-priority based on the Criminisi algorithm. The improved algorithm demonstrates better relationship between the data term and the confidence term for the optimization of the priority than the classical Criminisi algorithm. By comparing the effect of the inpainted images with different structure, conclusion can be drawn that the optimal priority should be chosen properly for different images with different structures.
文摘This paper proposes a novel exemplar- based method for reducing noise in computed tomography （CT） images. In the proposed method, denoising is performed on each block with the help of a given database of standard image blocks. For each noisy block, its denoised version is the best sparse positive linear combination of the blocks in the database. We formulate the problem as a constrained optimization problem such that the solution is the denoised block. Experimental results demonstrate the good performance of the proposed method over current state-of-the-art denoising methods, in terms of both objective and subjective evaluations.
基金This work was supported by National Science Foundation of China(Nos.61401150,61602157 and 61872311)Key Science and Technology Program of Henan Province(Nos.182102210053 and 202102210167)Excellent Young Teachers Program of Henan Polytechnic University(No.2019XQG-02).
文摘In the exemplar-based image inpainting approach,there are usually two major problems:the unreasonable calculation of priority and only considering the color features in the patch lookup strategy.In this paper,we propose an image inpainting approach based on the structural tensor edge intensity model.First,we use the progressive scanning inpainting method to avoid the image filling order being affected by the priority function.Then,we use the edge intensity model to build the patches similarity function for correctly identifying the local image structure.Finally,the balance operator is used to restrict the excessive propagation of structural information to ensure the correct structural reconstruction.The experimental results show that the our approach is comparable and even superior to some state-of-the-art inpainting algorithms.
