A deviant transform based approach for color image registration

In this paper, an unusual form of image registration is proposed which focuses upon using various transforms for fast and accurate image registration. Image registration is the process of transforming different sets of data into one coordinate system. The data set can be a set of photographs, data from various sensors, from different times, or from different viewpoints. The applications of image registration are in the field of computer vision, medical imaging, military automatic target recognition, and in analyzing images and data from satellites. The proposed technique works upon satellite images. It tries to find out area of interest by comparing the unregistered image with source image and finding the part that has highest similarity matching. The paper mainly works on the concept of seeking water or land in a stored image. The proposed technique uses different transforms like Discrete Cosine Transform, Discrete Wavelet Transform, HAAR Transform and Walsh transform to achieve accurate image registration. The paper also focuses upon using normalized cross correlation as an area based technique of image registration for the purpose of comparison. The proposed algorithm is worked over various sizes of satellite images such as 256×256, 1024×1024 etc. The root mean square error is used as similarity measure. The experiment results show that the proposed algorithm can successfully register the template and can also process local distortion in high-resolution satellite images.