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Author Bertalmio, Marcelo ♦ Vese, Luminita ♦ Sapiro, Guillermo ♦ Osher, Stanley
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Decomposition Space ♦ Image Filling-in ♦ Bounded Variation ♦ Real Image ♦ Original Image ♦ Bounded Variation Image ♦ Image Space ♦ Second Function ♦ Filling-in Algorithm ♦ Developed Component ♦ Simultaneous Use ♦ Different Image Characteristic ♦ Texture Synthesis Technique ♦ Texture Filling-in Algorithm ♦ Basic Idea ♦ Novel Contribution ♦ Image Information ♦ Underlying Image Structure ♦ Simultaneous Filling-in ♦ Image Decomposition ♦ Possible Noise ♦ Texture Image ♦ First Function ♦ Different Basic Characteristic ♦ Texture Synthesis
Abstract An algorithm for the simultaneous filling-in of texture and structure in regions of missing image information is presented in this paper. The basic idea is to first decompose the image into the sum of two functions with different basic characteristics, and then reconstruct each one of these functions separately with structure and texture filling-in algorithms. The first function used in the decomposition is of bounded variation, representing the underlying image structure, while the second function captures the texture and possible noise. The region of missing information in the bounded variation image is reconstructed using image inpainting algorithms, while the same region in the texture image is filledin with texture synthesis techniques. The original image is then reconstructed adding back these two sub-images. The novel contribution of this paper is then in the combination of these three previously developed components, image decomposition with inpainting and texture synthesis, which permits the simultaneous use of filling-in algorithms that are suited for different image characteristics. The novelty in the approach is to perform filling-in in a domain different from the original given image space. Examples on real images show the advantages of this proposed approach.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2003-01-01