Intraprediction Complexity Control Algorithm Based on Visual Saliency

Autor: Nana Shan, Wei Zhou, Zhemin Duan
Rok vydání: 2022
Předmět:
Zdroj: Journal of Sensors. 2022:1-13
ISSN: 1687-7268
1687-725X
DOI: 10.1155/2022/5069775
Popis: Intraprediction is one of the most complex parts of High-Efficiency Video Coding (HEVC), because it selects the best prediction mode by calculating the cost of every Coding Unit (CU), which provides higher complexity of intracoding. Visual saliency map can show the attention regions of the human eyes, which is generated by certain static and space-time saliency detection method. By analyzing the percentage of coding time for different size CU, and the relation of visual saliency and CU depth, an intraprediction complexity control algorithm based on visual saliency is proposed in this paper. Based on the feature of the video and the target level, the saliency threshold is adapted to determine whether the current CU in the intraprediction processing should be split into smaller CUs or the division processing should be stopped early. Three samples were compared by the proposed algorithm and other algorithm, and the proposed algorithm has better performance in PSNR, BitRate, and coding time. Experimental results show that this algorithm can effectively control the coding complexity of intraprediction with minimal visual loss and can be applied to a number of scenarios, such as real-time video coding.
Databáze: OpenAIRE
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