A Method for Automatic Accurate Image Registration and Translation

Automatic image registration is still present challenge in several fields like computer vision and remote sensing applications. Image registration is the process of transforming different sets of data into one coordinate system. In this paper, we propose a method for Automatic accurate Image Registration through Histogram-Based Image Segmentation and translation (delineation) using Wiener filtering which allows for a more detailed histogram-based segmentation, rather than the traditional methods, and consequently to an accurate image registration. Proposed system is able to estimate the rotation and/or translation between two images- which may be multitemporal or multisensor-with small differences in the spectral content. The first dataset consists in a photograph and a rotated and shifted version of the same photograph, with different levels of added noise. This allows for the registration of pairs of images with differences in rotation and translation. Various applications of image registration are target recognition, monitoring global land usage using satellite images, matching stereo images to recover shape for navigation, and aligning images from different medical modalities