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In recent years, the low latency and high efficiency characteristics of edge computing have extensive applications in infrared imaging systems, which could effectively reduce operational costs. However, issues such as low contrast and blurry details in infrared images still needed to be addressed. To solve these problems, an edge infrared image enhancement algorithm based on Lagrange interpolation and multi-scale guided filtering was proposed. This algorithm consisted of two phases. In the first phase, the Lagrange interpolation algorithm was used to achieve non-uniform correction for infrared data in the edge end. The Lagrange nonlinear interpolation was more in line with the response curve of the infrared detector, which effectively solved the problem of non-uniform noise introduced during imaging. In the second phase, multi-scale guided filtering was employed to process the infrared image in a hierarchical manner. Multiple scales were used to extract various details from images, and by fusing these different detail layers, a richer detailed information was obtained. Experimental results demonstrated that, compared to 5 traditional algorithms, this algorithm outperformed the suboptimal algorithm by 15.2% in the enhancement measure evaluation metric and achieved a 7.9% improvement in the peak signal to noise ratio metric.
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Basic Information:
DOI：10.13705/j.issn.1671-6841.2023235
China Classification Code:TP391.41
Citation Information:
[1]CHEN Ming,MA Guoqiang,HUANG Wanwei ,et al.Infrared Image Enhancement Algorithm Based on Edge[J].Journal of Zhengzhou University(Natural Science Edition),2025,57(04):47-54.DOI:10.13705/j.issn.1671-6841.2023235.
Fund Information:
国家自然科学基金项目(62072414); 河南省重点研发与推广专项项目(212102210104,162102210214)
2024-05-21
2024-05-21
2024-05-21