Abstract: Image denoising has an increasing importance in digital image processing as digital images are usually corrupted by different noises during amplification and transmission. Impulse noises are added due to the errors in the transmission channel and sensors in the path. In this study, a new method for the removal of Random Valued Impulse Noise (RVIN) is proposed. The entire process includes noise pixel detection and denoising. Corrupted pixels are detected in the four steps and the median filtering is applied for this noisy pixels. In each step, noisy pixels are detected based on the pre-defined threshold values and median filtering is applied in each step. Noisy pixels are removed in the successive steps. The simulation results show that the proposed method shows better performance over compared algorithms both in terms of peak signal to noise ratio and mean absolute error.
K. Ashok and V.R. Vijaykumar, 2016. Adaptive Window Based Multi Stage Impulse Noise Detection for Removal of Random Valued Impulse Noise in Digital Images. Asian Journal of Information Technology, 15: 689-693.