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A robust algorithm for compression and reconstruction of infrared thermal image sequence

机译:压缩和重建红外热像序列的鲁棒算法

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Quickly and accurately processing and saving high resolution thermal image sequences is a key technique in the field of thermal wave nondestructive testing. Based on the theory of thermal wave attenuation, this paper proposed a simple, fast and anti-noise global compression and reconstruction algorithm and showed the ability to improve the reliability and speed. Firstly the new algorithm divides the thermal image spatially and classifies thermal sequence. Then each curve in different temperature drop periods was fitted and lastly the compression and reconstruction of thermal sequence is fulfilled simultaneously in space and time by using the typical classified curve parameters as the compression and reconstruction parameters of thermal sequence. To verify the effect of the new algorithm, the experiment and comparison were carried out. The results show that the algorithm is a rapid, accurate and reliable. Compared with the current fitting compression method, it not only has a strong compression and anti-noise ability but also improve the operation speed up to hundreds of thousands of times.
机译:快速,准确地处理和保存高分辨率的热图像序列是热波无损检测领域的一项关键技术。基于热波衰减理论,提出了一种简单,快速,抗噪声的全局压缩和重构算法,并具有提高可靠性和速度的能力。首先,新算法对热图像进行空间划分并对热序列进行分类。然后拟合不同温度下降时期的每条曲线,最后通过使用典型的分类曲线参数作为热序列的压缩和重建参数,在空间和时间上同时完成热序列的压缩和重建。为了验证新算法的有效性,进行了实验和比较。结果表明,该算法是一种快速,准确,可靠的算法。与目前的拟合压缩方法相比,它不仅具有强大的压缩和抗噪能力,而且还可以将运行速度提高数十万倍。

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