In order to improve the accuracy of color digital image segmentation under complex background,reduce the noise interference in image processing,as far as possible to shorten the running time,the need for complex background color image segmentation algorithm.The process of the current image segmentation algorithm in digital color image,only considering the brightness of image pixel values,without considering the spatial characteristics of the defects,the computational complexity is too large,affecting color digital image processing effect.For this reason,a color digital image segmentation algorithm based on random weight particle swarm is proposed.This algorithm adopts multi-scale filtering method to classify the data uniform,color image under complex background,which contains the brightness noise and non noise pixel values,structure elements and the local area of the image pixel intensity weighted density features.Optimization of multi segment graph segmentation segmentation for color digital image,using gradient information of color digital image in the smoothing term,weak boundary of color digital image segmentation results are removed,so as to achieve accurate segmentation of color digital image.Experimental results show that the proposed algorithm increases the contrast and signal-to-noise ratio of color digital image segmentation,and improves the accuracy of color digital image segmentation in complex background.%为了提高复杂背景下彩色数字图像分割的准确率,减少噪声对图像处理的干扰,尽可能的缩短运行时间,需要对复杂背景下彩色数字图像分割算法进行研究;当前图像分割算法在彩色数字图像分割的过程中,仅仅考虑了图像像素的亮度值,没有考虑其空间特征,存在计算的复杂性过大等缺陷,影响彩色数字图像处理效果;为此,提出了一种基于随机权重粒子群的复杂背景下彩色数字图像分割算法;该算法先采用多尺度均匀滤波方法,对复杂背景下彩色数据图像进行划分,其中包含噪声和不含噪声的像素点的亮度值、结构元素以及局部区域内的图像像素加权亮度密度特征;采用多段图分割获取彩色数字图像的优化分割,在平滑项中代入彩色数字图像梯度信息,对彩色数字图像分割结果中的弱边界进行剔除,从而实现准确的彩色数字图像分割;实验仿真证明,所提算法增加了彩色数字图像分割的对比度和信噪比,提高了复杂背景下彩色数字图像分割的准确性.
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