A Video Coding Scheme Based on Bit Depth Enhancement With CNN
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Date
2023-06
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Addis Ababa University
Abstract
Raw 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.