This article introduces a novel infrared image enhancement algorithm, Heat-HE, which combines the histogram equalization algorithm with the laser cladding thermal field distribution law. By applying the grayscale world, automatic white balance, and Heat-HE algorithms to infrared images, the algorithm’s performance is evaluated using two evaluation indicators: average peak signal-to- noise ratio and average structural similarity. The experimental results demonstrate that the Heat-HE algorithm outperforms the comparison algorithm in terms of average peak signal-to-noise ratio, average structural similarity, and average running time. The Heat-HE algorithm efficiently removes noise and non-defective areas in infrared images, resulting in more intuitive and clear defect contours.
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