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Publication - Professor David Bull

    Enhanced Video Compression Based on Effective Bit Depth Adaptation

    Citation

    Zhang, A, Afonso, M & Bull, D, 2019, ‘Enhanced Video Compression Based on Effective Bit Depth Adaptation’. in: 2019 26th IEEE International Conference on Image Processing (ICIP 2019). Institute of Electrical and Electronics Engineers (IEEE)

    Abstract

    This paper presents a novel Convolutional Neural Network (CNN) based effective bit depth adaptation approach (EBDA-CNN) for video compression. It applies effective bit depth down-sampling before encoding and reconstructs the original bit depth using a deep CNN based up-sampling method at the decoder. The proposed approach has been integrated with the High Efficiency Video Coding reference software HM 16.20, and evaluated under the Joint Video Exploration Team Common Test Conditions using the Random Access configuration. The results show consistent coding gains on all tested sequences, with an average bitrate saving of 6.4%, based on Bjøntegaard Delta measurements using PSNR.

    Full details in the University publications repository