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    An FFT-Based technique and best-first search for image registration
    (2008-12-01)
    Samritjiarapon, Olan
    ;
    Chitsobhuk, Orachat
    The image registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different time, from different sensors, or from different viewpoints. One of the major challenges related to image registration is the estimation of large motion, when input images contain small overlapped area. Common image registration using the search algorithm can accurately finds large motion but requires high computation cost due to large search space. Fourier-based technique is an alternative approach since it can rapidly achieve the registration results through its FFT algorithm. However, only Fourier-based technique cannot produce the correct results in the case of large translation. Thus, this paper presents a Fourier-based technique cooperated with best-first search algorithm to analyze the correct translation between two input images. The Fourier-based technique is used to estimate the candidate translations to decrease searching space while best-first search algorithm is used to further search for the correct translation. The proposed technique can estimate large translations, scalings, and rotations in images by an extension of well-known phase correlation technique. The experimental results using various image details show the accuracy of the proposed technique to detect large translations compared to the other techniques in frequency domain. © 2008 IEEE.
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    Image registration using hough transform, phase correlation and best-first search algorithm
    (2007-12-01)
    Chunhavittayatera, Siwaphon
    ;
    Chitsobhuk, Orachat
    This paper presents image registration using a combination of Hough transform, phase correlation and best-first search algorithm to estimate rotation and translation parameters. These parameters are used to register input images and create a seamless representation of the registered image. In the first step, the translation of angles are pre-calculated based on ID phase correlation in Hough space and used as candidate angles. Then, best-first search algorithm is applied to obtain the best translation of angle from candidate angles, which is used to de-rotated the input images. In the second step, the translation in x-y axis is computed using 2D phase correlation. Finally, the input images are registered using the estimated translation parameter. The experimental results using various image details and sizes show the accuracy of the proposed technique to detect the translation parameters. The best-first search algorithm can help to increase the precision of rotation parameter after Hough transform and phase correlation while require less amount of processing time compared to full search algorithm.