superresolution_v_2[1].0

双目视觉经验总结，希望后面的不要犯错误。(Binocular visual experience summary, make no mistake behind.)

说明：  本程序是用matlab实现的CLBP源码(The source code of CLBP implemented by matlab)

说明：  SIFT的MATLAB源码，由加州大学的一位博士编写。(SIFT the MATLAB source code, from the University of California, prepared by Dr. A.)

Apprehend Screen Capture Component Version 4.2 A non-visible component to capture images. Freeware with source. Includes Four Demos with source and EXE s. 3,550 KB. 10/09/2005

matlab实现图像处理的程序，这是一个关于脑扫描图像分割的程序，很完整(matlab image processing procedures to achieve, this is a brain scan on the image segmentation process, it is a complete)

图像检测的算法，Faster R-CNN算法，先对整张图像进行卷积计算，然后通过感兴趣区域池化层(RoI Pooling Layer)将选择性搜索算法推荐出来的候选区域和卷积网络计算出的特征映射图进行融合，得到候选区域对应的特征矢量，这种共享卷积计算的操作极大地减少了卷积计算的次数。而且这些特征矢量的维度统一，方便后续的分类工作。通过感兴趣区域池化层处理卷积特征，并将得到的特征送往两个并行计算任务进行训练，分类和定位回归。通过这些方法和改进的框架，Fast R-CNN 用更短的训练和测试时长，取得了比 R-CNN 更好的效果(Faster R-CNN algorithm first convolutes the whole image, then fuses the candidate regions recommended by the selective search algorithm and the feature mapping maps calculated by the convolution network through the RoI Pooling Layer to get the corresponding feature vectors of the candidate regions, which greatly reduces the number of convolution calculations. Moreover, the dimension of these feature vectors is unified, which facilitates the subsequent classification work. The convolution feature is processed by the pooling layer of the region of interest, and the obtained feature is sent to two parallel computing tasks for training, classification and positioning regression. Through these methods and improved framework, Fast R-CNN uses shorter training and testing time and achieves better results than R-CNN.)

对图像采用DCT变换后，进行图像去噪的算法(Image denoise by DCT)

Downsample image console program using opencv.

对图像添加各种噪声 高斯噪声 淑盐噪声(Add a variety of image noise, Gaussian noise, noise, salt-sook)

直方图均衡化的实现，RGB直方图均衡化，直方图归一化。(Histogram equalization to achieve, RGB histogram equalization, histogram normalization.)