ronghe

IMAQPLOT is a simple demonstration of previewing video data using the toolbox s TimerFcn callback. IMAQPLOT also allows users to integrate the video preview into any MATLAB GUI. These are capabilities that are present in the toolbox s PREVIEW command, but are presented here as a demonstration of TimerFcn callback. Using toolbox callback properties, you can configure a video input object to generate a live image plot display. Do you want a basic preview window created for you? Simply call: obj = videoinput( matrox , 1) obj.TimerFcn = @imaqplot obj.TimerPeriod = 0.1 obj.FramesPerTrigger = Inf start(obj) Do you want to add a preview window to an existing GUI? Simply provide IMAQPLOT a handle to an image object and it will update it for you: obj = videoinput( dt , 1) obj.TimerFcn = {@imaqplot, hImage} obj.TimerPeriod = 0.1 obj.FramesPerTrigger = Inf start(obj)

实现了用LSB嵌入水印，还有两种水印分析方法：X2和信息量分析法(Achieved using LSB embedding the watermark, there are two kinds of watermarks analysis methods: X2 and the amount of information analysis)

P0701：细胞边缘检测 P0702：癌细胞形态学分析 P0703：癌细胞颜色分析 比较适合Matlab图像处理初学者(P0701: Edge Detection P0702: cell morphology analysis P0703: analysis and comparison of color cancer cells Matlab image processing for beginners)

时频分析的toolbox的guide，可以用于<Matlab时频分析技术及其应用>一书(time-frequency analysis of the toolbox the guide, can be used)

语音信号去噪，在MATLAB开发环境下，对含噪声的语音信号进行小波变换，实现语音增强的功能。(The speech signal denoising, wavelet transform, the noisy speech signal in the MATLAB development environment, Speech enhancement functions.)

对图像执行自适应中值滤波，中值滤波器开始大小为3*3(Adaptive median filter)

This paper presents a new approach to image segmentation using Pillar K-means algorithm. This segmentation method includes a new mechanism for grouping the elements of high resolution images in order to improve accuracy and reduce the computation time. The system uses K-means for image segmentation optimized by the algorithm after Pillar. The Pillar algorithm considers the placement of pillars should be located as far from each other to resist the pressure distribution of a roof, as same as the number of centroids between the data distribution. This algorithm is able to optimize the K-means clustering for image segmentation in the aspects of accuracy and computation time. This algorithm distributes all initial centroids according to the maximum cumulative distance metric. This paper evaluates the proposed approach for image segmentation by comparing with K-means clustering algorithm and Gaussian mixture model and the participation of RGB, HSV, HSL and CIELAB color spaces.

该文件为整数规划过程涉及的matlab程序段，包含割平面法及枚举法(This file is an integer planning process involves matlab program segments, including cutting plane method and the enumeration method)

solves 1d linear wave eq. by 4th order 13 point DRP scheme

说明：  viterbi 解码程序，用matlab编写。希望对大家有用。(viterbi decoding process, using matlab write. Hope to be useful.)