Gray level weighting centroid method for holographic data storage

Abstract

A gray level weighting centroid method for holographic data storage is disclosed. Firstly, a first gray level image having a plurality of blocks is received. Then, a convolution calculation is performed on a weight matrix and the image, so as to obtain a second gray level image having a plurality of blocks each having a gray level value. The gray level values are divided into a bright gray level value and a dark gray level value by a threshold value, so as to convert the second gray level image into a thresholding image and find the positions of the borders of the blocks corresponding to the bright gray level value. Next, the blocks surrounded by the positions of the borders and respectively used as a centroid block are found by making the positions of the borders correspond to the first gray level image. Finally, the centroid block is calculated to obtain a centroid point.