Automatic image registration through the segmentation of images pre-processed by joint histogram analysis

摘要

A wide variety of automatic image registration methods have been proposed in the last years. However, under the scope of remote sensing applications, geometric correction is still mostly a manual work. A methodology for automatic image registration is proposed, which consists in three major steps: pre-processing, segmentation, and registration. The considered pre-processing is a new method, which is an iterative process based on a joint histogram analysis. Regarding the segmentation stage, global thresholding and a new method were used. The later comprises global thresholding and distance transforms in a single method. For both methods the following object properties were extracted: area, major and minor axis lengths of the adjusted ellipse and perimeter. The registration phase incorporates the matching of corresponding objects, a template matching technique to compute the distance between each pair of matched objects, and the computation of the transformation function parameters. The used dataset consisted in the pairs ETM+/ASTER, ETM+/SPOT and Orthophoto/IKONOS. The proposed methodology allows for the registration of a pair of images with translation and rotation effects, and to some extent with different spectral content, leading to a subpixel accuracy. Furthermore, it has been shown that the proposed pre-processing method allowed for the achievement of suitable segmented objects for later matching, even using global thresholding.