Uncoded Video Data Stream Denoising in a Binary Symmetric Channel

Abstract

In this paper, a method for denoising an uncoded video stream in a binary symmetric channel is considered. When a bit of information is damaged, noise similar to impulse noise occurs with a certain probability. This work considers a model for transmitting visual data through a binary symmetric channel, where the noise characteristic corresponds to impulse noise distributed over the image with random values. Both random variables are distributed uniformly, both in brightness and in spatial location. In the proposed method, the distorted pixel is detected by comparing pixels inside the filter mask. Pixels are compared by their brightness value, and the remoteness of pixels within the detector area is also taken into account. The distance between pixels is calculated using the Euclidean metric. The local area of the filter takes into account pixels from the previous and next frames. Video frame recovery is performed using adaptive median filtering. A comparison was made with known methods. Based on the mean square error (MSE) and structural similarity index (SSIM) characteristics, it was shown that the proposed method copes with the task of denoising visual data better than the known methods.