High dynamic range (HDR) video compression and distribution

• Main Author: Mir, Junaid
• Other Authors: Fernando, Warnakulasuriya
• Published: University of Surrey 2017
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.731176

The continuous challenge of capturing and representing the high fidelity representation of the real-world scene on display devices to invoke true-to-life visual sensations has been the driving force behind the development of High Dynamic Range (HDR) imaging technologies. HDR imaging technologies enables the capture, storage and display of the light levels and colours inherent in the original capture of content. By doing so, it enables the HDR video to provide the sensation and quality which is closer to the seamless and immersive real-world appearance. However, existing conventional display devices being Low Dynamic Range (LDR) in nature and multimedia delivery technologies being designed and optimized for the 8-bit LDR video signal, does not support HDR video visualization and distribution, respectively. In this thesis, we explore how to exploit and utilize the existing multimedia delivery technologies for HDR video distribution keeping in view the need for backward-compatibility with already existing LDR displays. Unlike LDR video, HDR video utilizes higher bit-depth to faithfully preserve the luminance dynamic range encountered in the real-world scene and thus, cannot be distributed through current 8-bit video distribution infrastructure. Further, although HDR information can be utilized for rendering a closer to real-world LDR representation, this cannot be done by the LDR video player and display devices due to the incompatibility with HDR video. These challenges are addressed in our first contribution. We propose a two-layer scalable HDR video distribution method which is backward-compatible with the existing encoders and with ubiquitous LDR display devices. The base layer in the proposed method carries the LDR representation for LDR displays, generated from the HDR video. Whereas, the extension layer encodes the HDR information as a 8-bit video signal. An efficient mapping function is employed in the extension layer to improve the coding efficiency of the extension layer which in turn improves the HDR video quality in comparison to the other backward-compatible HDR video distribution methods. A review and performance evaluation of the state-of-the-art HDR video distribution methods is presented in our second contribution. This was done to categorize and critique the existing HDR video distribution methods in order to contribute to ongoing HDR video distribution standardization efforts which are presently impeded by the lack of comprehensive performance evaluation. 5 HDR video distribution methods, including ones in contention for being standardized as HDR video distribution method, were evaluated to present the performance assessment and behaviour of these methods for HDR video sequences having different characteristics. We showed that the performance of HDR video distribution methods is generally affected by the dynamic range and spatio-temporal characteristics of the HDR videos. Further, apart from identifying the most suitable distribution method for HDR video, we also highlighted the discrepancy in the prediction of HDR quality measured through the different HDR quality metrics employed. In our last contribution, we first presented the novel usage of the Perceptual Transfer Function (PTF) for improving and optimizing the compression performance of the state-of-the-art video compression standard; High Efficiency Video Coding (HEVC), for the HDR video compression. The PTF is utilized in the Rate-Distortion Optimization (RDO) process and results in an improved coding performance in terms of the Rate-Distortion efficiency for HDR video compression. We showed that using a PTF which is backward-compatible with the LDR transfer function can improve the HEVC compression efficiency which implies that HEVC needs to be optimized for the HDR video compression. Based on these observation, we further optimized the HEVC RateControl (RC) algorithm for the HDR video compression. A new λ-QP relationship is proposed which better estimates the relation between the HDR distortions and the bitrate utilized. As a result, intelligent bitrate allocation to the coding levels is achieved keeping in view the characteristics of the HDR content which results in an improved HDR quality at the same bitrate in comparison to the default RC algorithm for the HDR video.