F_matlab

图像融合中pan图像和多光谱融合的四种方法（IHS PCA 小波 小波结合PCA）和融合效果的评价指标计算（信息熵、Q4等指标）(Image fusion of the pan and multi-spectral image with four methods (IHS PCA wavelet wavelet combined PCA) and fusion effect evaluation method)

生成相机标定所用的方格图，用于相机标定使用(Generates the grid chart used to calibrate the camera)

基于FFT的配准程序，用在图像配准中的粗匹配中，对噪声、图像中物体发生运动等极为鲁棒！ (FFT-based registration procedure, used in image registration in the coarse matching, noise, motion and other image objects occur very robust!)

　对经典的二值化方法Ostu 算法和Bernsen 算法中存在的缺点进行了分析, 提出一种结合Canny 算子的图像 二值化方法.该方法综合考虑了边缘信息和灰度信息, 通过边缘附近种子点在高阈值二值化图像中的填充和低阈值 图像对它的修补而得到二值化结果图像, 较好地解决了经典二值化方法中存在的抗噪能力差、边缘粗糙、伪影现象 等缺点.实验结果证明, 该方法能够较好地解决低对比度图像和目标像素灰度不均匀图像的二值化问题(The disadvantage of the classical binary method Ostu Bernsen algorithm and algorithms exist were analyzed, one binding Canny operator image binarization method. This method considers the edge information and gray information, through seed near the edge point padding and a low threshold image to its repair in a high threshold binary image to obtain a binary result image, it solves the noise immunity classical binary method exists difference, rough edges, artifacts phenomenon and other shortcomings. the experimental results show that this method can solve the low-contrast image and the target image pixel gray uneven binary problem)

首先利用形态学开运算将图像中小于结构元素的亮点去掉，利用源图像与处理后的图像作差，对差图像进行阈值分割，得到二值图像，将二值图像中的一些干扰区域去掉，提取二值图像中的圆形区域，并在源图像上对小目标进行标记，实现对圆形亮目标的检测(Remove the area in the image smaller than structural element by morphologic open operation，receive image A，original image subtract image A，threshold segmentation for difference image，receive binary image，remove the interference region in the binary image，then extract circular area，and sign the target in the original image. Realize the circular bright target detection)

本算法先将彩色图像变换成灰度图像，在进行基于区域生长法进行图像分割(It segmented image with region growing. Then local adaptation luminance was computed via region-based bilateral filter. It outputted low dynamic range images in conjunction with tone mapping operator. )

说明：  Pattern Recognitn : Role of Digital Image Processing in Morphology

基于TensorFlow图像处理的小测试，里面的代码自己尝试过都可以运行。(Based on the TensorFlow image processing test, the code can run if it has tried.)

本文是基于最新的模糊C均值彩色图像分割方法改进得来的新算法(This article is based on the fuzzy c-means clustering color image segmentation method of the latest paper)

说明：  图形图像出来库文件，挺好用的，直接包含进工程就可以用了 (Graphic images from the library files, good used directly included into the project can be used)