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首页> 外文期刊>International Journal of Innovative Computing Information and Control >AN ADAPTIVE SQUARED GRADIENT ALGORITHM FOR AUTOFOCUSING OF THERMAL CAMERAS
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AN ADAPTIVE SQUARED GRADIENT ALGORITHM FOR AUTOFOCUSING OF THERMAL CAMERAS

机译：自动对焦的自适应平方梯度算法

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摘要

The aim of this study is to select from the autofocusing algorithms developed for visible image devices such an algorithm that is the most successful for thermal image devices. For this purpose, 500 different thermal images were processed by the widely used autofocusing algorithms such as Variance, Autocorrelation, Brenner and Squared Gradient, and the average rate of successful autofocusing for each algorithm was determined. From these results, it was derived that the best performance for thermal images is provided by the Squared Gradient algorithm. The analysis of the results of experiments showed that the success of the Squared Gradient algorithm is significantly affected by the resolution of the thermal images. Therefore, we developed this algorithm so that it can be adaptive to the resolution of the thermal image camera to be autofocused. Due to this improvement, the average rate of successful autofocusing for thermal images has been increased from 87 to 96 percent.
机译：这项研究的目的是从为可见光图像设备开发的自动聚焦算法中选择一种对热图像设备最成功的算法。为此，通过广泛使用的自动对焦算法（如方差，自相关，布伦纳和平方梯度）处理了500个不同的热图像，并确定了每种算法的自动对焦成功率。从这些结果可以得出，平方梯度算法可为热图像提供最佳性能。对实验结果的分析表明，平方梯度算法的成功受到热图像分辨率的显着影响。因此，我们开发了此算法，使其可以适应要自动对焦的热像仪的分辨率。由于此改进，热图像自动对焦的平均成功率已从87％提高到96％。

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