Research on low contrast image enhancement technology

Jiale Yao; Xiangsuo Fan; Yixun Chen; Wuchao Li

doi:10.1117/12.2626557

20 December 2021 Research on low contrast image enhancement technology

Jiale Yao, Xiangsuo Fan, Yixun Chen, Wuchao Li

Proceedings Volume 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021); 121550A (2021) https://doi.org/10.1117/12.2626557
Event: International Conference on Computer Vision, Application, and Design (CVAD 2021), 2021, Sanya, China

Abstract

When studying the machine vision of engineering machinery, it is found that the target detection algorithm has a low detection rate when dealing with the photos of night scene. In order to solve this problem, the image is enhanced before entering the neural network. This paper compares the common gray transformation image enhancement methods such as nonlinear transformation, linear transformation, logarithmic transformation and contrast stretching. By adjusting parameters, the four algorithms achieve the best results in dealing with pictures in dark environment. The comparative experimental results show that the image effect using contrast stretching technology is most similar to the image in daily environment. The image processed by contrast stretching can be easily recognized by the target detection algorithm to achieve the research purpose.

Citation Download Citation

Jiale Yao, Xiangsuo Fan, Yixun Chen, and Wuchao Li "Research on low contrast image enhancement technology", Proc. SPIE 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021), 121550A (20 December 2021); https://doi.org/10.1117/12.2626557

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