Saliency

c++特征提取，提取图像当中的红色灯笼。。。(c++ feature extraction, image extraction among red lanterns)

基于AdaBoost的人脸检测程序代码(是用c++编写的)(AdaBoost-based face detection program code (written with c++))

本代码实现的功能：24位位图（BMP）的灰度化。具体实现过程：打开图像文件,找到数据区(每3个字节代表一个象素的R,G,B值),循环扫描,根据RGB的权重,计算出灰度值. 如果要得到256色灰度图,则要新建一个调色板,修改信息头和文件头.(Realize the function of the code: 24-bit bitmap (BMP) of the gray. Concrete realization of the process: Open the image file, locate the data area (3 bytes per pixel on behalf of a R, G, B values), cyclic scan, according to the weight of RGB, gray value is calculated. If you want to get 256 colors grayscale, would create a new palette, modify the header and file header information.)

天津工业大学课程设计，内容包含vs2010对图像的灰度化，二值化，边缘检测。包含单纯c语言编写的对图像的灰度化，二值化，边缘检测的一个.C文件，可以直接用vc6.0运行，也可以直接在DSP上运行，还包含一份详细的设计报告。(Tianjin Polytechnic University curriculum design, content includes vs2010 grayscale image binarization, edge detection. Contains pure c language for image graying, binarization, edge detection is one. C file that can be run with vc6.0 can also be run directly on a DSP, also contains a detailed design report.)

静态画图，可以改变图形边框颜色与矩形或椭圆的填充颜色(Static drawing, you can change the fill color graphics border color and rectangular or oval)

人脸检测：可自动检测人脸，速度还可以吧！(Face Detection : can automatically detect faces and can also speed!)

说明：  压缩感知的经典代码，包括观测，稀疏表示，重建，其中观测用的高斯观测矩阵，稀疏用的DCT，重建用的OMP算法(Compressed sensing of the classic code, including observations, sparse representation, reconstruction, observed with a Gaussian observation matrix, sparse use of the DCT, re-use of the OMP algorithm)

可以实现bmp图象的sobel边缘检测运算，并含有可图象重建功能。简单，易懂，使用了DIB接口，适合作数字图象处理的初学者作参考(Bmp images can be achieved sobel edge detection operator, and contains the reconstruction of functional images. Simple, understandable, the use of the DIB interface, suitable for beginners of digital image processing for information)

英文原本经典计算机图形学教程，PPT格式，很好的学习材料和上课资料(English was the classic computer graphics course, PPT format, good learning materials and school information)

Pyramid methods in image processing