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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.)

N-FINDR算法 端元提取 读取MNF降维后的影像数据 读取MNF降维后的影像数据( using N-FINDR end-member extraction)

北航图像处理demo，目前集成了从色彩转换、彩色图像处理、灰度图像处理、二值图像处理、阈值分割、边缘检测、数学形态学方法、等多个组件(Northern image processing demo, now integrated from the color conversion, color image processing, gray-scale image processing, binary image processing, thresholding, edge detection, mathematical morphology, and many other components)

说明：  利用相位一致性提取图像边缘，K-means聚类后区域生长进行图像分割，附参考论文。(Using phase coherence image edge extraction, K-means clustering image after region growing segmentation, attached reference paper.)

偏微分方程_PDEs_模型在图像处理中的若干应用(_PDEs_ Model partial differential equations in image processing)

作者:J.Kittler and J.Illingworth KI阈值算法(Author：J.Kittler and J.Illingworth 1986)

数字识别PCA方法，对其它图像同样适用，程序简便。(Digital identification PCA method, on the other images of the same application, the program is simple.)

matching algorithm based on SIFT algorithm, extract feature points in use of Harris corner detection algorithm

这是基于稀疏表示的图像重建，用来做图像去模糊或超分辨，绝对可以用(Sparse Representation for Image Restoration)

BMP,ICO,JPG等图片格式转换，按照例子可以任意格式转换(BMP, ICO, JPG and other image format conversion, according to examples can be converted to any format.)