Study On Exemplar-based Image Inpainting Algorithm Based On Structure Tensor

With the promotion of computer technology,digital image inpainting technique,which reconstructs the missing region according to certain rules and the known information,obtains more and more attentions.Firstly,the background and significance of image inpainting are introduced,and then the research status of the technology is briefly described too.Next,the second chapter gives several classical inpainting model and analyzes the contrast algorithms.Finally,the problems still existing in the exemplar-based inpainting algorithms are summarized and deeply analyzed.Based on study the shortcomings of the current exemplar-based inpainting algorithms such as the inaccuracy of similarity measure,the broken structure and the inconsistent texture,an image inpainting algorithm based on structure tensor and block-structured sparsity is designed.Firstly,the structural tensor is combined with the color to construct the similarity between two patches,which makes it possible to find more suitable matching blocks.And then,using the structure-tensor based similarity,the block-structured sparsity is defined to better distinguish structure region.The structure continuity can be effectively maintained due to more stable fill sequence.Finally,the structure tensor feature information is added as a sparse constraint item to the objective function to improve the sparse representation accuracy,thereby ensuring the consistency of the neighborhood information.Experimental results show that the proposed method can better measure the differences between two patches and maintain the structure coherence of the repaired results.The results repaired by inpainting algorithm based on structure tensor and block-structured sparsity still have structure incoherence,texture unclearness and the mismatching.To address these problems,an image inpainting algorithm combining two-dimensional information entropy and correlation coefficient is put forward.Firstly,the algorithm measures the complexity of patch using two-dimensional information entropy.Based on this,the priority is designed to ensure the structural connectivity;then the matching criteria is constructed by the correlation coefficient to improve the matching accuracy;finally,the update of confidence is improved so as to reduce errors accumulated.Experimental results show that the algorithm can reduce the mismatching while maintaining the structure coherence of results.In order to demonstrate the image inpainting algorithm,this paper designed an image display system using MATLAB GUI.Through the system,user can directly select the damage image to repair and output the repaired results.