apex_ditecpsf

采用协方差的方式计算相关系数，分析图片的相似性，然后对图像进行匹配(The covariance of the way of calculating the correlation coefficient, and analyze the image similarity, and then to do image matching )

说明：  ISAR三维成像算法,可以用于matlab平台进行仿真(ISAR Three dimensional matlab)

说明：  根据Itti视觉注意模型得到图像的显著区域。本算法简单并且对一般简单的图像能够提取出比较好的显著区域。(According to Itti visual attention model are significant regions in the image. The algorithm is simple and easy on the general good image to extract a significant area.)

牛顿环的干涉条纹，灰度图，含有反射图样和透射图样(Newton' s rings interference fringes, grayscale, with reflection and transmission pattern pattern)

python语言，使用卷积神经网络的特征做图像检索(image retrieval using CNN)

针对于三架飞机进行的异常检测的基础算法 RX异常检测(RX Anomaly Detection algorithm for anomaly detection based on three of the aircraft)

这是图像处理中HSV课件颜色特征提取（将H5等份，S,V分量各三等份）MATLAB源码。(This is the image processing in HSV color feature extraction software (to be H5 equal, S, V component of the third class) MATLAB source.)

说明：  使用matlab识别干涉条纹。通过形态学处理，识别干涉条纹数，并计算出条纹间距。内包含交互界面。(The interference fringes are identified by matlab. Through morphological processing, the number of interference fringes is identified and the fringe spacing is calculated. It contains an interactive interface.)

压缩感知CS——采用小波变换进行稀疏表示，高斯随机矩阵为观测矩阵，重构算法为OMP算法，对256*256的lena图处理，比较原图和OMP算法在不同采样比例(0.74、0.5、0.3)下的重构效果，并各运行50次，比较算法性能PSNR和每次的运行时间 (Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix and OMP algorithm as the reconstruction algorithm. Compare lena figure and the reconstruction results using OMP algorithm at different sampling ratio (0.74,0.50.3),then each runs 50 times, compare the performance of PSNR and each running time)

说明：  对图像进行伽马校正，可以有效提升图像 亮度和对比度，低于低照度图像现在小于1的参数，对于高亮度的图像选择大于1的参数可以有效调节图像亮度。(Gamma correction can effectively improve the brightness and contrast of the image. The parameters lower than the low illumination image are less than 1. For the high brightness image, the selection of parameters greater than 1 can effectively adjust the brightness of the image.)