Rate control bit allocation method based on saliency

Abstract

The invention provides a rate control bit allocation method based on saliency. The method comprises the following steps: computing each frame of image, so as to obtain a saliency map of each frame of image; computing the saliency weighted average of each maximum coded unit according to the saliency map of each frame of image; performing target bit allocation on each coded unit according to the ratio of the weighted average of each maximum coded unit to a saliency map of an uncoded unit; acquiring a lagrangian multiplier based on saliency through the introduction of approximate saliency distortion of an original image and a reconstructed image; adjusting subsequent frame-level bit allocation, so as to realize a rate control function. The method takes the fact that saliency maps guide the bit allocation of a current frame and distortion situation based on saliency before and after coding into account, thereby achieving guiding effect on the frame-level rate control of a subsequent frame, and capable of realizing rate control based on saliency in a maximum coded unit level and image level.

Description

technical field [0001] The invention relates to a method in the technical field of image processing, in particular to a significance-based code rate control bit allocation method. Background technique [0002] Video compression has made great progress in the past few decades. From the early H.261 to today's H.264 and HEVC, the video coding technology has evolved from generation to generation, and the coding structure of the hybrid coding framework has been roughly established. The evolution of various module technologies has greatly improved the performance of video encoding. The latest HEVC has achieved the requirement of 50% performance improvement compared with the previous generation encoder H.264. [0003] In the field of real-time communication, such as video conferencing, video streaming consumes a large amount of bandwidth. When the bandwidth itself is limited, the quality of the video will be seriously affected. To solve the problem of limited bandwidth, precise bi...

AI Technical Summary

Problems solved by technology

Although this method can reflect its final coded bits to a certain extent, it ignores the relationship between image contents, and cannot guarantee the quality of the areas that people generally care about in the image is protected when the bandwidth is limited.

At the same time, if only focusing on the quality of the ROI without considering the salient distortion of the entire image, the serious degradation of the quality of the non-ROI will cause people's attention to shift to those unimportant areas that should be ignored.

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