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matlab编写的harris程序,对初学者还是很有帮助的(harris program written in matlab, or helpful for beginners)

基于稀疏分解的欠定盲源分离，要求信号具有一定的稀疏性。(Based on sparse decomposition due to blind source separation, the signal has a certain sparseness.)

说明：  区域生长算法。不用手动选择种子点，可自动选择。(Image segmentation by growing region method. No manual selection of seed points, automatic selection)

一种红外图像自适应对比度增强方法的仿真，绝对的真实，看到那些骗下载分的人恶心。需要自适应修改阈值T和A1，A2的值(An adaptive contrast enhancement method of infrared image simulation, absolutely true, see those who cheat download points. Need adaptive modified threshold T and A1, A2)

说明：  主要颜色谱 计算主要的颜色来舍弃其他的颜色，用少数的颜色个数代替大多数进行聚类(Main color spectrum calculation primary colors to abandon other colors)

广义正交压缩感知的代码，实现了压缩感知与图像的重构(Generalized orthogonal compressed sensing code, to achieve compressed sensing and image reconstruction)

一个简单的HALCON计算圆心坐标的例子，C++代码格式，初学者适用！(A simple example of calculating coordinates HALCON, c++ code format, for beginners!)

对采样得到的180幅断层图像进行重建，并针对其中的一幅图像进行处理，并且统计图像中颗粒的大小和数目！(Tomographic images of 180 samples obtained were rebuilt, and for which an image processing and image size and number of particles statistics!)

图像局部放大功能。包括主要的三个消息处理函数，由鼠标拖动画出需放大区域，松开即将图像局部放大到整个客户区，能够实现层层放大。(enlarge images partial function. Including the three main message processing function, the mouse scrolling painted by the need to enlarge the regional, Loosen the forthcoming local enlarge images of the entire client area, can be achieved at every level to enlarge.)

说明：  傅立叶变换在图像处理中的重要作用： (A) 图像增强与图像去噪 绝大部分噪音都是图像的高频分量，通过低通滤波器来滤除高频噪声；边缘也是图像的高频分量，可以通过添加高频分量来增强原始图像的边缘； (B) 图像分割与边缘检测 提取图像高频分量 (C) 图像特征提取 形状特征：傅里叶描述子 纹理特征：直接通过傅里叶系数来计算纹理特征 其他特征：将提取的特征值进行傅里叶变换来使特征具有平移、伸缩、旋转不变性 (D ) 图像压缩 可以直接通过傅里叶系数来压缩数据；常用的离散余弦变换是傅立叶变换的实变换； (Fourier transform in the important role of image processing: (A) image enhancement and image denoising Most of all images of high frequency noise by low pass filter to filter out high frequency noise edge is the image of the high frequency components can be enhanced by adding high frequency components to the edge of the original image (B) Image segmentation and edge detection High frequency components extracted image (C) image feature extraction Shape features: Fourier descriptors Texture: directly through the Fourier coefficients to calculate the texture features Other features: The characteristic value extracted by Fourier transform to the characteristics of translation, scaling, rotation invariance (D) image compression Fourier coefficients can be directly compressed data commonly used discrete cosine transform is the Fourier transform of the real transformation 朗读显示对应的拉丁字符的拼音)