Video image enhancement method and device

Abstract

The invention discloses a video image enhancement method and device. The method comprises the following steps: dividing an image to be enhanced into a plurality of image blocks with the same size, acquiring the image information of the image blocks, acquiring a local histogram height threshold according to the image information, adaptively adjusting the contrast of the image blocks according to the local histogram height threshold, acquiring grey values of central pixel points of all image blocks according to a contrast adjustment result, acquiring the grey values of the central pixel points of non-image blocks in the enhanced image by interpolation, and outputting the enhanced image. The device comprises a division module, a computing module, a contrast adjusting module and an interpolation module. The method and the device disclosed by the invention are used for adopting corresponding local histogram height thresholds to enhance the contrast of different image blocks, uniform and sufficient tiling on the gray level can be realized, and the adaptability to different monitoring scenes is strong.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a video image enhancement method and device. Background technique [0002] Due to factors such as weather conditions, brightness conditions, and capture equipment, the nighttime surveillance video is not clear or even abnormally blurred, which is not conducive to monitoring and cannot meet the needs of applications. But nighttime video surveillance has practical application value, so nighttime video enhancement algorithm is worth studying. [0003] The video enhancement algorithm can be divided into two types: spatial domain-based video enhancement and frequency domain-based video enhancement according to the different processing spaces. Video enhancement based on frequency domain processes images through indirect operations in the transform domain of images. The most commonly used transform is the Fourier transform. Video enhancement based on the frequency...

AI Technical Summary

Problems solved by technology

This algorithm requires loops and has relatively high complexity, so it is not suitable for real-time enhancement processing of video streams

[0004] It can be seen that in the existing technical solutions, there are many gray levels that are not used in the common histogram equalization solution, and the underutilization of the gray levels is one of the reasons for the over-equalization

In addition, when using the classic equalization method for image enhancement on images with relatively high components at low gray levels, the effect will often be distorted.

The existing histogram equalization method has no way to control different parameters in different regions of the image to achieve better results

And because the complexity of existing technology algorithms is relatively high, real-time enhancement of video stream images at night cannot be realized, so it has little practical significance in video surveillance

Images