Implementation of cellular automata for impulsive noise reduction in grey scale images. (22nd October 2014) - Kumar, Tapas; Sahoo, G.
This paper presents a new cellular automata based filter with the ability to remove impulsive noise, while, simultaneously, preserving edges and image details efficiently. Noise reduction is one of the most commonly used operations in image analysis. It is considered to be an important application of image processing; digital images can be corrupted by different types of noise during the image acquisition or transmission. Several noise reductions have been proposed in literature for enhancing the images. In this paper, a new and optimal approach of noise reduction based on cellular automata has been proposed. The idea is simple but effective technique for noise reduction that greatly improves the performances of complicated images. To demonstrate the capability of our filtering approach, it was tested on several different image enhancement problems. Results are compared with other existing filtering technique in terms of Peak Signal to Noise Ratio (PSNR). The comparative analysis of various image noise reduction methods is presented and shown that cellular automata based algorithm performs better than all these techniques under almost all scenarios.