An image enhancement algorithm based on bivariate rational interpolation

This paper presented a new image enhancement algorithm. Large amounts of edge and texture information of the original image are lost by the traditional algorithm, and the edges of image include the most important information. Furthmore, the effect of image enhancement has been defined using the traditional interpolation algorithm. Sometimes the enhancement effect is not satisfying such as changing the local average gray level, decreasing the image contrast, and so on. But the image is not further enhanced. In order to slove the problems of traditional, A bivariate rational interpolation with parameters is used in the new algorithm. The value of the interpolating function at any point in the interpolating region can be modified under the condition that the interpolating data are not changed by selecting the suitable parameters. The image enhancement process is divided into two steps. Firstly, the membrane energy is used for image denoising. According to the maximum and minimum membrane energy value of the interpolation surface, the noise pixel is detected. The noise point gray value can be replaced by the weighted mean membrane energy value, under the constraint of the rank-ordered mean of the filter window during noise removal. Image noise removal can be implemented by re-interpolation. Secondly, the denoised image enhancement is implemented using the surface control. The experiment results show that the new arithmetic outperforms the conventional one in edge information preserving and local image further enhanced.