We present the development of a cross-correlation algorithm for correlating objects in the long wave, mid wave and short wave Infrared sensor arrays. The goal is to align the images in the multisensor suite by correlating multiple key features in the images. Due to the wavelength differences, the object appears very differently in the sensor images even the sensors focus on the same object. In order to perform accurate correlation of the same object in the multi-band images, we perform image processing on the images so that the features of the object become similar to each other. Fourier domain band pass filters are used to enhance the images. Mexican Hat and Gaussian Derivative Wavelets are used to further enhance the features of the object. A Python based QT graphical user interface has been implemented to carry out the process. We show reliable results of the cross-correlation of the objects in multiple band videos.
Recommended citation: Thomas Lu, Tien-Hsin Chao, Kang (Frank) Chen, Andrew Luong, Mallory Dewees, Xinyi Yan, Edward Chow, Gilbert Torres, } “Cross-correlation and image alignment for multi-band IR sensors”, Proc. SPIE 9845, Optical Pattern Recognition XXVII, 984505 (20 April 2016); doi: 10.1117/12.2224694; https://doi.org/10.1117/12.2224694