Macroblock layer bit allocation optimization method based on visual attention

Abstract

The invention provides a macroblock layer bit allocation optimization method based on visual attention. The macroblock layer bit allocation optimization method based on visual attention comprises a step 1 of determining whether a macroblock belongs to a foreground region or a background region and detecting a motion region, a step 2 of detecting a structural texture region by use of a gradient, and a step 3 of allocating the target bits of the macroblock. The method is characterized in that based on the visual attention characteristics of an HVS (Human Visual System), firstly, the motion region attracting visual attention in an image is extracted by use of a motion vector of the macroblock in a reference frame in combination of an inter-frame difference method and the position of the current macroblock, and then the texture region is detected by use of an average gradient, and finally, the target bit allocation of the macroblock is optimized according to the region of the macroblock in the image. The algorithm involved in the macroblock layer bit allocation optimization method based on visual attention has the same coded image quality as a JVT-G012 algorithm; the fluctuation of a video sequence PSNR (Peak Signal to Noise Ratio) is reduced, the entire coded image is kept stable in objective quality, and meanwhile, excellent subjective quality of the coded image is also achieved.

Description

technical field [0001] The invention belongs to the technical field of video processing and provides a visual attention-based macroblock layer bit allocation optimization method. Background technique [0002] In H.264 / AVC, the compressed video quality is usually evaluated by objective standards (such as peak signal-to-noise ratio, PSNR). The subjective visual experience of the human eye can only reflect the general quality of the video. Visual psychology studies have shown that the subjective perception of images and videos by the human visual system (HVS) is affected by various factors such as brightness, contrast, color, texture, motion, and position, and there are masking effects of space, time, and color. In a complex visual scene, the attention of the human eye is quickly attracted by the area of ​​interest in the scene, and the information is prioritized. This process is called visual attention. Research on the mechanism of visual attention shows that when the human ...

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Literature H.Li, Z.B.Wang, H.J.Cui, K.Tang, An improved ROI-based rate control algorithm for H.264 / AVC, IEEE ICSP2(2006) 16–20.; Y.Liu, Z.G.Li, Y.C.Soh, M.H. Loke, Conversational video communication of H.264 / AVC with region of interest concern. IEEE ICIP (2006) 3129–3132. Video coding based on the region of interest (region of interest, ROI), through the skin color of the object in the video image, people Faces and hands are detected and tracked to extract ROIs. Since the ROIs in these methods are extracted from specific video content, their application scenarios are limited.

Literature Chen ZZ, Han JW, Ngan KN(2006)Dynamic bit allocation for multiple video object coding.IEEETrans Multimed8(6):1117–1124.Yang L,Zhang L,Ma S,Zhao D(2009)A ROI quality adjustable rate control scheme for low bitrate video coding.Picture Coding Symposium,Chicago,USA,May.06-08. Assign target bits according to different objects in the video sequence. This object-based coding method is more flexible than the ROI-based method, but it must be effective Distinguishing and extracting different objects in a video sequence requires high computational complexity and is not suitable for real-time video encoding and transmission

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