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Reliable band-to-band registration of Multispectral Thermal Imager data using multivariate mutual information and cyclic consistency

机译:使用多变量互信息和循环一致性可靠地对多光谱热像仪数据进行波段间配准

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摘要

In multispectral imaging, automated cross-spectral (band-to-band) image registration is difficult to achieve with a reliability approaching 100%. This is particularly true when registering infrared to visible imagery, where contrast reversals are common and similarity is often lacking. Algorithms that use mutual information as a similarity measure have been shown to work well in the presence of contrast reversal. However, weak similarity between the long-wave infrared (LWIR) bands and shorter wavelengths remains a problem. A method is presented in this paper for registering multiple images simultaneously rather than one pair at a time using a multivariate extension of the mutual information measure. This approach improves the success rate of automated registration by making use of the information available in multiple images rather than a single pair. This approach is further enhanced by including a cyclic consistency check, for example registering band A to B, B to C, and C to A. The cyclic consistency check provides an automated measure of success allowing a different combination of bands to be used in the event of a failure. Experiments were conducted using imagery from the Department of Energy's Multispectral Thermal Imager satellite. The results show a significantly improved success rate.
机译:在多光谱成像中,很难以100%的可靠性实现自动跨光谱(带间)图像配准。当将红外配准到可见图像时,尤其是这样,在对比度相反的情况很常见并且经常缺乏相似性。已经证明,使用互信息作为相似性度量的算法在存在对比度反转的情况下可以很好地工作。但是,长波红外(LWIR)波段与较短波长之间的相似性较弱仍然是一个问题。本文提出了一种使用互信息测度的多元扩展同时注册多幅图像而不是一对图像的方法。这种方法通过利用多个图像而不是一对图像中的可用信息来提高自动注册的成功率。通过包括循环一致性检查(例如,注册频带A到B,B到C和C到A)来进一步增强此方法。循环一致性检查提供了自动成功的度量,允许在频带中使用不同的频带组合。故障事件。实验是使用来自能源部多光谱热成像仪卫星的图像进行的。结果显示成功率显着提高。

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