Video bit enhancement method based on attention mechanism

Abstract

The invention discloses a video bit enhancement method based on an attention mechanism. The method comprises the following steps: establishing a video bit enhancement model based on the attention mechanism; randomly selecting a set number of original video sequence groups with high bit depth from an image enhancement database to construct a training data set; training a video bit enhancement modelbased on an attention mechanism by using the constructed training data set; selecting a video sequence group from an image enhancement database to form a test set, and testing the trained attention mechanism-based video bit enhancement model; applying a zero filling algorithm to video signals needing to be enhanced to obtain high-bit-depth video signals, sequentially inputting the high-bit-depthvideo signals into the tested video bit enhancement model based on the attention mechanism by taking five frames as a group, and adding output results of the high-bit-depth video signals to middle frames of the correspondingly input video sequence groups so as to sequentially and correspondingly obtain enhanced middle frames. According to the invention, the semantic attention matrix related to thetarget feature map is generated on the feature level, so that the perception visual quality is improved.

Description

technical field [0001] The invention relates to a video bit enhancement method. In particular, it involves an attention-based video bit enhancement method. Background technique [0002] Multimedia resources such as images and videos carry a wealth of information, and people can quickly understand what is happening in the outside world through images and videos. Since the birth of video recording devices and display devices, people have been working on how to obtain and display higher quality images and videos. In order to pursue a better visual experience, people have proposed a high dynamic range (High Dynamic Range, HDR) technology, which uses a higher dynamic range and more bit depth (usually 10 or 12 bits) to represent a pixel. Images and videos with high dynamic range can show richer colors, finer color transitions, and more realistic texture details. At present, with the development of technology, ultra-high-definition displays and HDR displays are becoming a common...

AI Technical Summary

Problems solved by technology

[0004]The above bit enhancement methods are all image-oriented, if they are applied to video sequences with low bit depth, the redundant information of the front and rear frames of the video cannot be obtained well The use of high-bit video sequences, and the resulting high-bit video sequences will appear inter-frame flicker and other phenomena

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