Reference frame-based low illumination monitoring image enhancement method

Abstract

The invention provides a reference frame-based low illumination monitoring image enhancement method comprising the following steps: a reference frame and a low illumination image to be enhanced are obtained from a monitoring video, neighboring frames of the low illumination image is extracted, an illumination component of a background image is calculated, an illumination component of the image to be enhanced is calculated, reflection components of the low illumination image and a plurality of the neighboring frames are extracted, and an enhancement result of the low illumination image to be enhanced can be obtained after denoising operation via fusing operation. Via the reference frame-based low illumination monitoring image enhancement method, the illumination component of the image to be enhanced can be estimated accurately, color fidelity of the enhancement result can be improved, noise interference can be lowered, sharpness and a recognizable degree of the low illumination monitoring image can be improved, and forceful support can be provided for the monitoring image to assist criminal investigation.

Description

Technical field [0001] The present invention belongs to the technical field of image enhancement, and relates to low-illuminance image enhancement related technologies, in particular to a low-illuminance monitoring image enhancement method based on a reference frame. Background technique [0002] As the construction of "safe cities" progresses nationwide, video surveillance technology is playing an increasingly critical role in maintaining public safety. However, because surveillance cameras often shoot in low-quality lighting environments, such as rainy weather at night and during the day, the surveillance videos captured are often of low quality and blurry. The image taken in a low-quality lighting environment is a low-light image. Therefore, in practical applications, there is an urgent need for quality improvement of low-illuminance images with a large number of surveillance scenes in order to improve their clarity and recognition, and to give play to the criminal investigat...

AI Technical Summary

Problems solved by technology

Second, although the reference-based low-illuminance image enhancement method introduces other reference image information, the fusion-based enhancement algorithm adopts the form of dividing the low-illuminance image into two parts, the background and the foreground, which are often enhanced due to the foreground contour extraction. The inaccuracy leads to unnatural outline of the enhancement result; the enhancement algorithm based on daytime reference contains background image texture information in the estimated illuminance component during the enhancement process, which leads to the confusion of foreground and background texture in the enhancement result; the enhancement algorithm based on big data relies on a large number of images Sample data, it takes time to train the enhancement model, and the current enhancement model is good for the simulation of low brightness and noise enhancement, but the enhancement result for the actual low illumination image is still not ideal

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