Image Resolution Conversion by Optimized Adaptation of Interpolation Kernels

A. Fujii, K. Kameyama, T. Kamina, Y. Ohmiya, and K. Toraichi (Japan)


resolution conversion, adaptive interpolation kernel, Par ticle Swarm Optimization, Fluency information theory


There are various methods for the resolution conversion of a digital image. However, these methods have problems of edge blur and jaggy noise. The resolution conversion by adaptive interpolation kernels was proposed to solve these problems. However, jaggy noise and edge blur still arise, because the parameters that determine the shape of interpo lation kernels are empirically set. In this work, we obtain the optimal parameters for interpolation kernel adaptation using Particle Swarm Optimization. The results show our approach is promising for high quality resolution conver sion.

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