Image Registration is the process of fusing or overlaying of two images of the same scene that were taken at
different times and/or from different viewing angles and/or by sensors with different modality or resolution.
The variations in the imaging environment induce the difference between the images of the same scene. In our
situation, we have two images of the same scene taken with different sensors, one image is in the visible domain
and the other is an IR image. The images are captured using a visible camera and a thermal camera by placing
the two devices adjacent to each other and taking the images simultaneously without a significant change in
time and spatial location. Using image registration we project the visible image into the infrared image to
rectify both images to the same co-ordinate system. This is done to match the sensor output and then produce
an information product from the two which can be used to further analyze and assess the scene. In this paper
we use the conformal log polar mapping (CLPM) for image registration. The CLPM is invariant to changes in
rotation and scale: rotational changes map to a shift along one of the axes and scale changes a shift long the
other. Thus the CLPM for the two images mentioned above should essentially be the same even though the
two were taken from different sensors. The amount of shift can be used to determine the angle of rotation of
the rotated image with respect to the original image. The same holds for the change in scale of the two images
were the shift along the x-axis or the magnitude axis in the log polar mappings of the two images can be used
to find the scaling factor between the two images. This method calculates the transformation parameters for
rectifying the reference image to the original image or vice-versa, and can be used to register the two images
that vary in phase and scale. In this paper, we present a robust approach for image registration that uses
these shifts to compute the parameters representing rotation and scale change, and registers a pair of images.
An application of this approach is in detecting wave height for efficient navigation of a watercraft where the
images to be fused are taken from multiple sensors which are fixed on the craft. The wave parameters can be
determined by looking at the common features in the edge profile of the images taken from different sensors.
The goal here is to provide real time assessment of the sea state from the information obtained from the sensor
suite for possible route and speed changes to increase safety and improve ride quality.