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Video Quality Preservation Based on Deep Neural Network

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Submitted:

18 November 2024

Posted:

19 November 2024

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Abstract
This paper presents a method for preserving the quality of video compressed with video codecs. The video codecs used in this article are H.264/AVC (Advanced Video Coding) and its successor H.265/HEVC (High Efficiency Video Coding). The aim of the article is to present a method for enhancing the video quality for high compression values by preprocessing video frames using Deep Neural Network (DNN). The proposed method reduces the degree of image quality degradation caused by lossy video compression by improving the detail quality of the output video frames after decompression. The proposed method improves video quality for high QP (Quantization Parameter) values beginning from 25 and above. Compared to the popular trend of improving the video quality of already degraded video, the presented method attempts to improve the quality by modifying the image before the compression process by the video codec. The image is modified by DNN to obtain the lowest possible loss of video quality, represented by quality coefficients, but above all by the visual reception of the video by the viewer, enabling increased perception of more details in conditions of high video compression.
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Subject: Computer Science and Mathematics  -   Computer Vision and Graphics
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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