dcm2bmpandbmp2dcm

说明：  用VC实现数字减影算法，通过模板匹配，再对两幅图像相减，即用盈片中减去蒙片，从而实现突出血管区域的目的。【源码加文档说明】(Using VC to achieve digital subtraction algorithm, template matching, and then the subtraction of two images, that the film with surplus minus mask, in order to achieve the purpose of highlighting vascular region. 【Source】 plus documented)

这是图象缩放的代码，对于学习图像的朋友应该有所帮助(This is the image scaling code for the study should help the image of a friend)

vc++ 数字图象处理 很好用我看了以后收益非浅希望大家喜欢(vc digital image processing with very good after I read greatly benefit hope you like)

这是一款适用于初学者的应用程序,它可以帮助我们处理图形图像(This is a beginner for the application, it can help us to deal with graphic images)

对火焰图像进行二值化 边缘检测 链码提取 并计算火焰图像的面积和周长 绝对好用！(Binarization flame image edge detection chain code extraction and absolutely easy to calculate the area and perimeter of the flame image!)

该源码为目标检测和跟踪算法 包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (The source code for target detection and tracking algorithm include: 1 Static background background prediction target detection 2 Static background frame difference method for target detection 3. Mean Shift tracking method 4 multi-target tracking methods focus)

由VC实现画矩形、椭圆和随手画功能，对图像处理人员会有帮助(paintings by VC rectangular, oval and hand painting functions, image processing staff to be helpful)

说明：  此程序为地震层析成像的LSQR算法，此算法用来解反问题。(This procedure for seismic tomography LSQR algorithm, the algorithm used to solve inverse problems.)

过特定人语音情感数据库的建立；语音情感特征提取；语音情感分类器的设计，完成了一个特定人语音情感识别的初步系统。对于单个特定人，可以识别平静、悲伤、愤怒、惊讶、高兴5种情感，除愤怒和高兴之间混淆程度相对较大之外，各类之间区分特性良好，平均分类正确率为93.7 。对于三个特定人组成的特定人群，可以识别平静、愤怒、悲伤3种情感，各类之间区分特性良好，平均分类正确率为94.4 。其中分类器采用混合高斯分布模型。(The system of speech emotion recognition)

高斯平滑滤波实例，高斯滤波实质上是一种信号的滤波器，其用途是信号的平滑处理，我们知道数字图像用于后期应用，其噪声是最大的问题，，由于误差会累计传递等原因，很多图像处理教材会在很早的时候介绍Gauss滤波器，用于得到信噪比SNR较高的图像（反应真实信号）。 (Instance of the Gaussian smoothing filter, Gaussian filter is essentially a signal filter, its purpose is to smooth processing of the signal, we know that the digital image for the late application, the noise is the biggest problem, the error accumulated transfer reason, a lot of image processing textbooks will be introduced at an early Gauss filter for higher SNR of the image (real response signal).)