Rational Based Particle Swarm Optimization for Digital Image Interpolation
Image interpolation is a common problem in image applications. Although many magnification algorithms have been proposed in the literature, these methods suffer from the effects of imperfect reconstruction to some degree, most often; these effects manifest themselves as jagged contours or blurred edges in the image. In this paper novel information system, which contains crisp data for decision making, is investigated. It develops an evolutional Vector Rational Filter Particle Swarm Optimization VRF PSO fitting algorithm to self extract the near optimum estimator to achieve the application of color image interpolation. The VRF PSO interpolator combines the advantage of the VRF and the efficient Particle Swarm Optimization (PSO) It is a more accurate approximation than other linear and nonlinear interpolation functions. Quantitative and qualitative simulation results are also presented to demonstrate the superior performance of color image magnification.