Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior.

Lingli Guo,Zhenhong Jia,Jie Yang,Nikola K Kasabov

doi:10.3390/s22010085

Abstract

In low illumination situations, insufficient light in the monitoring device results in poor visibility of effective information, which cannot meet practical applications. To overcome the above problems, a detail preserving low illumination video image enhancement algorithm based on dark channel prior is proposed in this paper. First, a dark channel refinement method is proposed, which is defined by imposing a structure prior to the initial dark channel to improve the image brightness. Second, an anisotropic guided filter (AnisGF) is used to refine the transmission, which preserves the edges of the image. Finally, a detail enhancement algorithm is proposed to avoid the problem of insufficient detail in the initial enhancement image. To avoid video flicker, the next video frames are enhanced based on the brightness of the first enhanced frame. Qualitative and quantitative analysis shows that the proposed algorithm is superior to the contrast algorithm, in which the proposed algorithm ranks first in average gradient, edge intensity, contrast, and patch-based contrast quality index. It can be effectively applied to the enhancement of surveillance video images and for wider computer vision applications.

Highlights

With the development of science and technology, surveillance video plays an important role in the field of public safety
Videos are composed of multiple single-frame images presented in time, so video enhancement can be achieved by enhancing each low illumination image
The results of qualitative and quantitative evaluations show that our method can significantly improve the video captured in low illumination conditions and has better results than other methods

Summary

Introduction

With the development of science and technology, surveillance video plays an important role in the field of public safety. In low light conditions at night, the light entering the video device is insufficient, which results in a bad visual effect on the recorded video. These negative effects may include low brightness and contrast, color distortion, and poor visibility. Many enhancement algorithms have been proposed based on certain characteristics of low illumination images. To improve the brightness of low illumination images, some methods directly modified the size and distribution of pixels, such as gray transformation methods and histogram equalization (HE) methods [1,2]. Researchers proposed a series of enhancement algorithms based on Retinex [6] to avoid the problem of directly adjusting the pixel values. The algorithm is prone to the phenomenon of insufficient/excessive enhancement, which leads to the loss of image details

Methods

Results

Discussion

Conclusion