Description

Impulse noise reduction from corrupted images plays an important role in image processing. This problem will also affect on image segmentation, object detection, edge detection, compression, etc. Generally, median filters or nonlinear filters have been used for noise reduction but these methods will destroy the natural texture and important information in the image like the edges. In this paper, to eliminate impulse noises from noisy images, we used a hybrid method based on cellular automata (CA). In the first step, based on statistical information, noisy pixels are detected by CA and by using filtering we filter the noise window finally restore the pixels. Regularly; CA is used for systems with simple components where the behavior of each component will be defined and updated based on its neighbors. The proposed method is characterized as simple, robust and parallel which keeps the important details of the image effectively. The proposed approach has been performed on well-known gray scale test images and compared with other conventional and famous algorithms, is more effective.