Perceptual Encoding Optimization Algorithm Guided by Human Eye Focusing Mechanism

Perceptual coding algorithms play a crucial role in eliminating visual redundancy in video compression. Despite their promising results, there remains potential for further optimization, particularly in leveraging human visual characteristics for rate control and effectively applying just noticeable distortion (JND)a threshold defining human visual sensitivity to changes. In this paper, we propose a novel HEVC rate control scheme inspired by the focusing mechanism of the human visual system (HVS). By integrating saliency and focal distance information, we construct a focusing factor and incorporate it into the encoding framework. This focusing factor serves as a key parameter for rate control, optimizing LCU-level bit allocation and enhancing video coding efficiency. Furthermore, we combine the focusing factor with a JND-based model to design a Gaussian filter that smooths nonfocused areas, reducing background redundancy while enhancing visual quality. The proposed algorithm is implemented on HM16.7, and experimental results show bitrate savings and PSNR improvements ranging from 0.1 to 0.5 dB compared to state-of-the-art algorithms. Additionally, subjective evaluations confirm significantly enhanced visual quality at equivalent bitrates.