A Feature Based Complexity Model for Decoder Complexity Optimized HEVC Video Encoding
The complexity of the novel video compression algorithms is a major contributor for the increased demand of processing and energy resources for video playback in consumer electronic devices. Therefore, a decoder complexity reduction mechanism is proposed which constitutes a model that predicts the decoder's complexity requirements to decode the HEVC encoded bit streams with a 4.2% average prediction error and a decoder complexity optimized encoding algorithm, which reduces the decoding complexity by an average of 28.06% and 41.19% with a -1.91 dB and -2.46 dB impact to the BD-PSNR for the low delay P and random access configurations, respectively.
Presented atConference paper published in 2017 IEEE International Conference on Consumer Electronic (ICCE), available at: https://doi.org/10.1109/ICCE.2017.7889357.
Published in2017 IEEE International Conference on Consumer Electronics (ICCE)
VersionAM (Accepted Manuscript)
CitationMallikarachchi, T., Talagala, D.S., Fernando, A. and Kodikara Arachchi, H. (2017) 'A Feature Based Complexity Model for Decoder Complexity Optimized HEVC Video Encoding', IEEE International Conference on Consumer Electronic (ICCE), Las Vegas, USA, 8-10 January. DOI: 10.1109/ICCE.2017.7889357.
Cardiff Met Affiliation
- Cardiff School of Technologies