The increased demand for high quality video evidently elevates the bandwidth require- ments of the communication channels being used, which in return demands for more efficient video coding algorithms within the media...
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The increased demand for high quality video evidently elevates the bandwidth require- ments of the communication channels being used, which in return demands for more efficient video coding algorithms within the media distribution tool chain. As such, High Efficiency Video Coding (HEVC) video coding standard is a potential solution that demonstrates a significant coding efficiency improvement over its predecessors. HEVC constitutes an assortment of novel coding tools and features that contribute towards its superior coding performance, yet at the same time demand more compu- tational, processing and energy resources; a crucial bottleneck, especially in the case of resource constrained Consumer Electronic (CE) devices. In this context, the first contribution in this thesis presents a novel content adaptive Coding Unit (CU) size prediction algorithm for HEVC-based low-delay video encoding. In this case, two in- dependent content adaptive CU size selection models are introduced while adopting a moving window-based feature selection process to ensure that the framework remains robust and dynamically adapts to any varying video content. The experimental results demonstrate a consistent average encoding time reduction ranging from 55% – 58% and 57% – 61% with average Bjontegaard Delta Bit rate (BDBR) increases of 1.93% – 2.26% and 2.14% – 2.33% compared to the HEVC 16.0 reference software for the low delay P and low delay B configurations, respectively, across a wide range of content types and bit rates. The video decodingcomplexity and the associated energy consumption are tightly coupled with the complexity of the codec as well as the content being decoded. Hence, video content adaptation is extensively considered as an application layer solution to reduce the decodingcomplexity and thereby the associated energy consumption. In this context, the second contribution in this thesis introduces a decodingcomplexity- aware video encoding algorithm for HEVC using a novel d
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