Minimizing the Perceptual Impact of Visual Distortion in Scalable Wavelet Compressed Video

This paper considers the efficacy of a class of intra-channel contrast masking models and proposes a simple extension to increase their effectiveness in capturing perceptual diversity in complex stimuli. "Perceptual diversity" encapsulates the idea that our perceptual response to visual distortion varies, depending not only on where quantization errors occur, but also how they coincide with structural elements that constitute a video frame. We offer a fresh perspective on perceptual modeling and identify factors that limit visual optimization performance. We find that the perceptual impact of suprathreshold visual distortion cannot be fully assessed based on contrast alone, hi this work, we introduce a context-adaptive masking slope to complement the basic functions of our perceptual model. This versatile feature allows visual sensitivity to be emphasized, or suppressed, in a manner which reflects the perceptual significance of local distortion in a video. Finally, we propose a visual optimization strategy for embedded video coding based on a perceptual mapping and distortion scaling approach. This technique mitigates the noise shaping effects due to motion-compensated temporal synthesis.