Improved Motion Estimation Algorithm Based on Fourier-Mellin Transform and Keren Algorithm
邓建青 Deng Jian-qing, 刘晶红 Liu Jing-hong · Chinese Journal of Liquid Crystals and Displays · 2011
Because Super-resolution image reconstruction requires high precision and high speed of motion estimation of image,so it is proposed to make three improvements with the traditional Fourier-Mellin transform and Keren algorithm of motion estimation:to avoid the shortcoming of Fourier-Mellin transformation(bad registration accuracy of image with poor details),edge detection of the image in advance is made;as Fourier-Mellin transformation is used for coarse estimation,the number of sampling points is reduced during the log polar transform with the angle accuracy below 1°,which greatly reduced the size of matrix,and increased the rate of registration;with Fourier-Mellin transformation being used for coarse estimation firstly,do not need to use the pyramid of Keren algorithm,but only need one layer for motion estimation so that to reduce the registration time.The simulation in VC++ shows that the method is effective in maintaining the advantages of Fourier-Mellin transform and Keren algorithm,at the same time improving the speed of motion estimation.Accordding to the experiment,with the traditional algorithm it needs 3.53 s to do motion estimation of image with 328 multiply 500 pixels,but needs 1.15 s with the improved algorithm which greatly improve the speed.