software

读取RAW格式文件，将其转换为BMP格式文件并存储，主要实现灰度图像的转换(Read the RAW format, convert it to BMP format file and stored, mainly to achieve the conversion of grayscale images)

使用K均值做聚类分析来进行图像分割,把原始图像转换到HSV空间做聚类分析(use k-means clustering to segment the image)

时隙 ALOHA（Slotted ALOHA）算法是在纯ALOHA 算的基础上将时间分成了多个离散的时隙，被分割成的时隙的长度要大于标签所携带数据信息帧的长度(Slot ALOHA (Slotted ALOHA) algorithm is based on pure ALOHA time will be counted into the slot more discrete, divided into the slot length is greater than the length of the data label information carried by the frame)

说明：  本设计为基于MATLAB的指纹识别系统。本设计系统主要对指纹图像进行三方面处理：图像预处理、特征提取和特征匹配。图像预处理包括四个步骤：图像灰度化、滤波增强、二值化、细化，对指纹图像进行预处理后，去除了原图像的冗余部分，方便后续的识别处理；特征提取主要是提取指纹图像细化后的端点和分叉点；特征匹配是利用两个指纹的图像进行特征点比较，来确定两幅图像是否来自于同一手指。(This design is a fingerprint identification system based on MATLAB. This system mainly deals with fingerprint image in three aspects: image preprocessing, feature extraction and feature matching. Image preprocessing includes four steps: image grayscale, filter enhancement, binarization and thinning. After preprocessing the fingerprint image, the redundant part of the original image is removed for the convenience of subsequent recognition processing. Feature extraction is mainly to extract the endpoint and bifurcation points after thinning the fingerprint image. Feature matching is to determine the two images by comparing the feature points of the two fingerprint images Whether the image comes from the same finger.)

说明：  SAR运动目标成像，包含了多个点目标，结果比较清晰(SAR Moving Target Imaging)

说明：  图像处理案例，本程序是用matlab语言上基于多尺度形态学完成提取眼前节组织的功能(Image processing case, this program is based on multi-scale morphology using MATLAB language to complete the extraction of anterior segment tissue function.)

说明：  结合Retinex和CLAHE图像去雾，Retinex有ssr，msr，msrcr。(Combine Retinex and clean image to remove fog)

实现vieb算法处理,ViBe_Matlab 能够实现视频处理,利用MATLAB实现的VIEB算法(Implementation of vieb algorithm processing)

此压缩包包含了数字图像处理算法的基本M函数和ICE界面定制的M函数。(This package includes the digital image processing algorithms of the basic M function and ICE interface customized M function.)

介绍了粒子滤波目前主要应用领域, 最后对粒子滤波的发展提出了展望。(Describes the particle filter is currently the main application areas, and finally the development of particle filter raised prospects.)