A mixed noise filtering algorithm based on the genetic algorithm and L-filter

A novel algorithm for mixed noise filtering in image processing is presented, combing the genetic algorithm and L-filter. The algorithm based on central limit theorem estimates mixed noise model through inter-selecting region of interest in the image, and adds this mixed noise model to a small test image for rebuilding degraded process. Aiming at this test image, the genetic algorithm is used to optimize the weight coefficients of L-filter. Then the optimized weight coefficients are used in combination with image edge information to execute L-filter to the image. Experiments demonstrate that this method is better than Laplacian filter and median filter.