Night effect removal method for camera-collected video

Abstract

The invention discloses a night effect removal method for a camera-collected video, comprising the following steps of: collecting images of a same scene at daytime under various light conditions to form a set; training samples, creating a dictionary and setting a threshold; carrying out color model processing and denoising for an image collected at night; calculating a background image according to the threshold; successively obtaining the image of every frame of a streaming video collected at night; carrying out the color model processing and denoising to get a foreground image; integrating the foreground image with the background image; and removing the noise and storing integrated images in a new video file until the image of the last frame of the video stream is treated. The night effect removal method for the camera-collected video has simple processes, and high efficiency; is capable of effectively removing night effect of a monitoring video at night for a fixed scene and improving the contours and colors of the objects in the monitoring video, thereby enabling the effect of the whole image to be close to the image at daytime, obtaining detail information of the images easily, and obtaining a video effect close to that at daytime.

Description

[0001] technical field [0002] The invention relates to a video processing technology, in particular to a nighttime effect removal method for video collected by a camera. Background technique [0003] In terms of video processing technology, the traditional processing of night images is relatively simple, mainly by increasing the brightness of image pixels to increase the brightness of the entire image. [0004] Night image enhancement based on nonlinear inverse tone mapping. In recent years, various tone mapping algorithms have been developed. One of the complex algorithms is based on the method of contrast or gradient domain. These algorithms focus on the maintenance of contrast rather than the mapping of brightness. The idea of ​​this method originates from the fact that the human eye is most sensitive to contrast or the brightness ratio of different brightness regions. . This kind of tone mapping usually produces very sharp images due to better preservation of contras...

AI Technical Summary

Problems solved by technology

The demand for color and detail information in the picture cannot be met

Moreover, the price of infrared cameras is relatively high, which is not suitable for wide application.

Ordinary cameras are difficult to work normally at night, the brightness is low at night, the light is poor, and the quality of surveillance video is low

Video surveillance at night is particularly important for security and anti-theft work. There are few studies on New Year's Eve. For traditional cameras, this invention proposes a new method

Images