Paper
20 December 2021 Research on low contrast image enhancement technology
Jiale Yao, Xiangsuo Fan, Yixun Chen, Wuchao Li
Author Affiliations +
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.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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KEYWORDS
Image processing

Image enhancement

Detection and tracking algorithms

Intelligence systems

Neural networks

Target detection

Target recognition

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