A Video Coding Scheme Based on Bit Depth Enhancement With CNN

dc.contributor.advisorBisrat Derebssa (PhD)
dc.contributor.authorDaniel Getachew
dc.date.accessioned2023-12-14T14:51:42Z
dc.date.available2023-12-14T14:51:42Z
dc.date.issued2023-06
dc.description.abstractRaw or uncompressed videos take a lot of resources in terms of storage and bandwidth. Video compression algorithms are used to reduce the size of a video and many of them have been proposed over the years. People also proposed video coding schemes which works on top of existing video compression algorithms by applying down sampling prior to encoding and restoring them to their original form after decoding for further bitrate reduction. Down sampling can be done in spatial resolution or bit depth. This paper presents a new video coding scheme that is based on bit depth down sampling before encoding and use CNN to restore it at the decoder. However unlike previous approaches the proposed approach exploits the temporal correlation which exists between consecutive frames of a video sequence by dividing the frames into key frames and non-key frames and only apply bit depth down sampling to the non-key frames. These non-key frames will be reconstructed using a CNN that takes the key frames and non-key frames as input at the decoder. Experimental results showed that the proposed bit depth enhancement CNN model improved the quality of the restored non-key frames by an average of 1.6dB PSNR than the previous approach before integrated to the video coding scheme. When integrated in the video coding scheme the proposed approach achieved better coding gain with an average of -18.7454% in Bjøntegaard Delta measurements.
dc.identifier.urihttp://etd.aau.edu.et/handle/123456789/1003
dc.language.isoen_US
dc.publisherAddis Ababa University
dc.titleA Video Coding Scheme Based on Bit Depth Enhancement With CNN
dc.typeThesis

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