Feature preserving image interpolation by adaptive bidirectional flow |
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Authors: | Shujun Fu Jingnian Chen |
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Affiliation: | 1. Institute of Information Science,Beijing Jiaotong University,Beijing 100044,China;School of Mathematics and System Science,Shandong University,Jinan 250100,China 2. School of Arts and Science,Shandong University of Finance,Jinan 250014,China |
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Abstract: | Most image interpolation algorithms currently used suffer visually to some extent the effects of blurred edges and jagged artifacts in the image. This letter presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to enhance edges along the normal directions to the iso-phote lines (edges), while a normal diffusion is done to remove artifacts ("jaggies") along the tangent directions. In order to preserve image features such as edges, angles and textures, the nonlinear diffusion coefficients are locally adjusted according to the first order and the second order directional derivatives of the image. Experimental results on the Lena image demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations. |
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Keywords: | Anisotropic diffusion Bidirectional flow Directional derivatives Edge enhancement Image interpolation Inverse flow |
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