Information Bottleneck Driven Deep Video Compression—IBOpenDVCW
Video compression remains a challenging task despite significant advancements in end-to-end optimized deep networks for video coding. This study, inspired by information bottleneck (IB) theory, introduces a novel approach that combines IB theory with wavelet transform. We perform a comprehensive ana...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-09-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/26/10/836 |
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| author | Timor Leiderman Yosef Ben Ezra |
| author_facet | Timor Leiderman Yosef Ben Ezra |
| author_sort | Timor Leiderman |
| collection | DOAJ |
| description | Video compression remains a challenging task despite significant advancements in end-to-end optimized deep networks for video coding. This study, inspired by information bottleneck (IB) theory, introduces a novel approach that combines IB theory with wavelet transform. We perform a comprehensive analysis of information and mutual information across various mother wavelets and decomposition levels. Additionally, we replace the conventional average pooling layers with a discrete wavelet transform creating more advanced pooling methods to investigate their effects on information and mutual information. Our results demonstrate that the proposed model and training technique outperform existing state-of-the-art video compression methods, delivering competitive rate-distortion performance compared to the AVC/H.264 and HEVC/H.265 codecs. |
| format | Article |
| id | doaj-art-478b878a1ae04f02b490a36bc80fb0b8 |
| institution | OA Journals |
| issn | 1099-4300 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj-art-478b878a1ae04f02b490a36bc80fb0b82025-08-20T02:11:00ZengMDPI AGEntropy1099-43002024-09-01261083610.3390/e26100836Information Bottleneck Driven Deep Video Compression—IBOpenDVCWTimor Leiderman0Yosef Ben Ezra1Faculty of Electrical Engineering, Holon Institute of Technology, 52 Golomb Str., P.O. Box 305, Holon 58102, IsraelFaculty of Electrical Engineering, Holon Institute of Technology, 52 Golomb Str., P.O. Box 305, Holon 58102, IsraelVideo compression remains a challenging task despite significant advancements in end-to-end optimized deep networks for video coding. This study, inspired by information bottleneck (IB) theory, introduces a novel approach that combines IB theory with wavelet transform. We perform a comprehensive analysis of information and mutual information across various mother wavelets and decomposition levels. Additionally, we replace the conventional average pooling layers with a discrete wavelet transform creating more advanced pooling methods to investigate their effects on information and mutual information. Our results demonstrate that the proposed model and training technique outperform existing state-of-the-art video compression methods, delivering competitive rate-distortion performance compared to the AVC/H.264 and HEVC/H.265 codecs.https://www.mdpi.com/1099-4300/26/10/836deep video compressionwaveletsinformation bottleneckneural networks |
| spellingShingle | Timor Leiderman Yosef Ben Ezra Information Bottleneck Driven Deep Video Compression—IBOpenDVCW Entropy deep video compression wavelets information bottleneck neural networks |
| title | Information Bottleneck Driven Deep Video Compression—IBOpenDVCW |
| title_full | Information Bottleneck Driven Deep Video Compression—IBOpenDVCW |
| title_fullStr | Information Bottleneck Driven Deep Video Compression—IBOpenDVCW |
| title_full_unstemmed | Information Bottleneck Driven Deep Video Compression—IBOpenDVCW |
| title_short | Information Bottleneck Driven Deep Video Compression—IBOpenDVCW |
| title_sort | information bottleneck driven deep video compression ibopendvcw |
| topic | deep video compression wavelets information bottleneck neural networks |
| url | https://www.mdpi.com/1099-4300/26/10/836 |
| work_keys_str_mv | AT timorleiderman informationbottleneckdrivendeepvideocompressionibopendvcw AT yosefbenezra informationbottleneckdrivendeepvideocompressionibopendvcw |