Lightweight Video Super-Resolution for Compressed Video
نویسندگان
چکیده
Video compression technology for Ultra-High Definition (UHD) and 8K UHD video has been established is being widely adopted by major broadcasting companies content providers, allowing them to produce high-quality videos that meet the demands of today’s consumers. However, high-resolution not an easy problem be resolved in near future due limited resources network bandwidth data storage. An alternative solution overcome challenges downsample or at transmission side using existing infrastructure, then utilizing Super-Resolution (VSR) receiving end recover original quality content. Current deep learning-based methods fail consider fact delivered viewers goes through a decompression process, which can introduce additional distortion loss information. Therefore, it crucial develop VSR are specifically designed work with compression–decompression pipeline. In general, various information compressed utilized enough realize model. This research proposes highly efficient making use from decompressed such as frame type, Group Pictures (GOP), macroblock type motion vector. The proposed Convolutional Neural Network (CNN)-based lightweight model suitable real-time services. performance extensively evaluated series experiments, demonstrating its effectiveness applicability practical scenarios.
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ژورنال
عنوان ژورنال: Electronics
سال: 2023
ISSN: ['2079-9292']
DOI: https://doi.org/10.3390/electronics12030660