Medical image restoration approach using cultural algorithms

In medical image processing, the image degradation often occurs. The image restoration is to recover the original image from its noisy and blurred version. A restoration approach using cultural algorithms for medical images is presented in this paper. First of all, the representation of image degradation model is built. Secondly, an image is encoded as an individual; the fitness of an individual is defined. An algorithm based on the principle of cultural algorithms is presented for obtaining the ideal images from the blurred image. The algorithm consists of the population space, the belief space, and the communication protocol that describes the exchange mode of knowledge between the population space and belief space. A few type of knowledge, such as the situational knowledge and the normative knowledge etc., are used. The images with better quality are obtained by the evolution of populations. The experimental results show that the image restoration approach proposed in this paper can obtain the good approximations of the original image.