Comparative Analysis of Interframe Filtering Algorithms for Video Sequences Distorted by Additive Noise
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Abstract
One of the essential requirements for the operation of technical systems for digital video sequence processing is the reduction of the negative impact of interference that arises in video images during their acquisition or transmission through communication channels. Suppression of interference and improvement of the signal-to-noise ratio is relevant for applications in which, in addition to visual analysis of the obtained observations, corresponding algorithms for automatic data processing may also be employed. Filtering typically serves as a fundamental component of image processing, while the choice of specific algorithms depends on the requirements for their computational complexity and their ability to suppress the corresponding type of interference.
This paper presents a comparative analysis of the algorithms applied to solve the problem of interference suppression modeled as additive white Gaussian noise that distorts the sequence of digital images. The specific implementation features of denoising methods based on the inter-frame averaging procedure are provided. Mathematical expressions describing the corresponding image denoising procedures are presented, and the selected approaches are characterized with an indication of their advantages and disadvantages. The research is conducted by simulation in the MATLAB software environment using synthesized data based on homogeneous textured images described by a Gaussian random field model. Quantitative indicators of the filtering results for the synthesized video sequence with predefined parameters are obtained. Graphs of the mean square deviation of the filtering error are presented, enabling assessment of the degree of interference suppression achieved by the applied approaches. To ensure the possibility of visual subjective evaluation of the data obtained through the implemented algorithms, examples of denoised frames of the model video image are provided.
The obtained results demonstrate the applicability of the investigated methods to video data filtering tasks aimed at interference suppression and may be used in the development of algorithmic support for software modules for processing video sequences characterized by a high level of inter-frame correlation, as well as in scientific tasks related to the development of video denoising methods.
