这是本人毕设时所作的医学图像处理源代码，供初学者参考

这是用VC便携的DCT变换，很好很实用，希望可以为你带来帮助。-This is the DCT-portable with VC, very good very practical, hoping to bring you help.

完整的多级滤波图像处理算法，利用FPGA实现，利用硬件结构实现算法能够满足苛刻的实时性要求。-Complete multi-level filtering image processing algorithms using FPGA realization algorithm using hardware structure able to meet the demanding requirements of real-time.

Matlab图像处理的典型指令，包含应用测试-Matlab image processing typical commands, including application testing

视频逐行转隔行算法,一般用于电视解交错算法评估-video algorithm about progressive to interlace

vc编写三惟投影变换以及二为线段以及多边形裁减！-A 3D projection transform,2D segment of line and polygon cut down programed with vc

采用多孔trous算法(undecimated wavelet transform)实现小波变换，用的是一维信号 -The use of porous trous algorithm (undecimated wavelet transform) the realization of wavelet transform, using a one-dimensional signal

算法特点： 1）可检测正面正负15度人脸； 2）支持多人脸检测； 3）经过优化后对尺寸为320×240的视频图像检测速度达15帧/秒； 4）支持灰度图像人脸检测、低照度视频图像人脸检测。 测试条件：要求计算机安装USB CMOS视频摄像头及驱动程序。 运行要求：可执行程序exe与配置文件FPD.ini在同一个目录下。 -Algorithm characteristics: 1) to deliver people testing positive face of plus or minus 15 2) support for more than face detection 3) after the optimized size of 320 × 240 video image detection rate of 15/s 4) to support the gray Image Face Detection, illumination video face detection. Test conditions: installation requires a computer USB CMOS video camera and driver. Operation requirements: exe executable files and configuration FPD.ini in the same directory.

figure 4.2a single pluse 3-D uncertainty plot pulsewidth is 2 seconds。 Figure 4.2b. Contour plot corresponding to Fig. 4.2a. Figure 4.2c. Single pulse 3-D ambiguity plot. Pulsewidth is 2 seconds. Figure 4.2d. Contour plot corresponding to Fig. 4.2c. -figure 4.2a single pluse 3-D uncertainty plot pulsewidth is 2 seconds. Figure 4.2b. Contour plot corresponding to Fig. 4.2a. Figure 4.2c. Single pulse 3-D ambiguity plot. Pulsewidth is 2 seconds. Figure 4.2d. Contour plot corresponding to Fig. 4.2c.

图像的快速傅立叶变换，基于VC++开发平台。-images of fast Fourier transform, based VC development platform.

This toolbox implements the algorithm in a fairly general way in a C file that can be called from Matlab. It allows to perform the traditional NL-means for denoising (for both B&W and color images) but also to use an arbitrary set of patches to perform the denoising. -This toolbox implements the algorithm in a fairly general way in a C file that can be called f rom Matlab. It allows to perform the traditiona l NL-means for denoising (for both B