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 isophote 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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Supported by the National Natural Science Foundation of China (No.60472033), the Key Laboratory Project of Information Science & Engineering of Railway of National Ministry of Railways, China (No.tdxx0510), and the Technological Innovation Fund of Excellent Doctorial Candidate of Beijing Jiaotong University, China (No.48007).
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Fu, S., Chen, J. Feature preserving image interpolation by adaptive bidirectional flow. J. of Electron.(China) 23, 154–156 (2006). https://doi.org/10.1007/s11767-005-0042-9
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DOI: https://doi.org/10.1007/s11767-005-0042-9