Spatiotemporal visual considerations for video coding
Human visual sensitivity varies with not only spatial frequencies, but moving velocities of image patterns. Moreover, the loss of visual sensitivity due to object motions might be compensated by eye movement. Removing the psychovisual redundancies in both the spatial and temporal frequency domains facilitates an efficient coder without perceptual degradation. Motivate by this, a visual measure is proposed for the purpose of video compressions. The novelty of this analysis relies on combining three visual factors altogether: the motion attention model, unconstrained eye-movement incorporated spatiovelocity visual sensitivity model, and visual masking model. For each motion-unattended macroblock, the retinal velocity is evaluated so that discrete cosing transform coefficients to which the human visual system has low sensitivity are picked up with the aid of eye movement incorporated spatiovelocity visual model. Based on masking thresholds of those low-sensitivity coefficients, a spatiotemporal distortion masking measure is determined. Accordingly, quantization parameters at macroblock level for video coding are adjusted on the basis of this measure. Experiments conducted by H.264 exhibit the effectiveness of the proposed scheme in improving coding performance without picture quality degradation.
eye movement visual masking h.264 adaptive quantization bit allocation spatiovelocity contrast sensitivity visual attention