Efficient Removal of Impulse Noise from Video Using Adaptive Threshold Algorithm

In digital image processing noise removal or noise filtering plays an important role, because for meaningful and useful processing images should not be corrupted by noises. In recent years, high quality televisions have become very popular but noise often affects TV broadcasts. Impulse noise corrupts the video during transmission and acquisition of signals. A number of denoising techniques have been introduced to remove impulse noise from images and video. Linear noise filtering technique does not work well when the noise is non-adaptive in nature and hence a number of non-linear filtering technique where introduced. In nonlinear filtering technique, median filters and its modifications where used to remove noise but it resulted in blurring of images. Therefore we propose an adaptive digital signal processing approach that can efficiently remove impulse noise from color video. In this algorithm, the pixel is replaced only if it is identified to be a noisy pixel by the proposed adaptive threshold algorithm otherwise the original pixel is retained. Thus it results a better filtering technique when compared to median filters and its modified filters. It is proved that the proposed algorithm is more suitable for high noise environment. The parameters Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) are measured for determining the visibility and similarity of output video frames.