针对现有的光斑质心算法无法直接处理含有离散噪声点的图像, 提出一种不依赖去噪预处理和噪声点剔除后处理, 本身具有抗单点噪声能力的光斑质心定位算法, 并通过现场可编程门阵列(FPGA)实现了该算法。首先分别标记背景像素、噪声像素和光斑像素; 然后通过对相邻像素标记的判断, 完成对当前像素的标记; 同时对属于同一光斑的像素进行质心参数累加, 但不累加和存储判断为真正噪声点的像素。与现有方法相比, 该方法能够充分利用FPGA的并行处理能力, 在图像像素输出的同时完成光斑质心提取和噪声点像素去除, 而且不需要存储预处理图像和噪声点像素, 节省了存储空间。该方法为由于图像传感器长时间曝光而引起的高亮度离散噪声光斑图像的处理提供了有效的途径。

A spot centroiding algorithm immune from noise pixels is proposed to improve the existing centroiding algorithms that can not process images with discrete noise pixels directly, and it is achieved by a Field Programmable Gate Array(FPGA). This algorithm does not depend on noise pre-process or post-process to eliminate noise pixels. Firstly, the algorithm marks the background pixel, noise pixel and the spot pixel, respectively, then each pixel is marked after it is compared with the neighbouring one. At the same time, centroid parameters that belong to the same spot are accumulated, while the real noise pixel is bypassed. Compared with currently existing algorithms, this method takes full advantage of the parallel processing ability of the FPGA. It can extract spot centroid coordinates and eliminate the noise pixel simultaneously when the image pixel is output, the pre-process image is not needed and the storage space is saved. This algorithm is especially suitable for processing the spot image with discrete and high-brightness noises caused by long exposure time.