Tp_images_Son

图像的自动拼接和缝补，采用sift算法作为匹配，是学习全景图像拼接的基础，大家可以下载下来看看(Automatic image stitching and sewing, using sift algorithm as a match, is the basis for learning panoramic image mosaic, you can download to see)

说明：  LSB算法在图像中隐藏文本信息，实现效果良好，分享给大家(The LSB algorithm hides the text information in the image to achieve good results and share it with everyone)

压缩文件中的代码可以读取图片并计算绿色植被的归一化植被指数，直接在IDL中打开即可使用(The code in the compressed file can read pictures and calculate the normalized vegetation index of green vegetation,and you can open it directly in IDL and use it.)

快速双边滤波器，对双边滤波器进行的改进，可以使用，对写论文的同学会有些帮助，可以参考看一下。(Rapid bilateral filter, to the improvement of bilateral filter, can be used, to write a paper of homecoming some help, you can refer to see.)

Retinex算法本质上就是一种基于光照补偿的图像增强算法, 能够对高动态范围图像进行增强。(Retinex algorithm is essentially an image enhancement algorithm based on illumination compensation, which can enhance the image of high dynamic range.)

BCS代码稀疏重构Lena.bmp图像，包中含有代码和图片本身，题主给了一定注释，便于CS初学者学习(BCS code sparsely reconstructs Lena. BMP image. The package contains code and image itself. The theme is given a certain comment, which is convenient for CS beginners to learn.)

用平均背景法去除背景，算法思想比混合高斯模型和codebook模型简单，适合提取背景变化较小的场景。用中值滤波去除掉产生的椒盐噪声(Average method to remove the background with the background, the algorithm thought codebook than the Gaussian mixture model and a simple model for extraction of small changes in background scene. With a median filter to remove salt and pepper noise generated)

说明：  内含M文件 利用对数比实现，两幅多时空SAR图像变化差异图 (Logarithm figure than the implementation differences )

Harris角点检测程序（内附示例图像），利用鼠标在图像上选择提取交点的区域，进行角点提取。程序语言简洁，利于初学者学习。(Harris corner detection procedures (with sample images), using the mouse in the image on the choice of extraction point of intersection of the region, for Corner Detection. Programming language is simple and conducive to learning for beginners.)

灰度图像的属性计算：利用bwlabel和regionprops函数对度量二值图像中目标对象的属性。(Attribute gray image: Using bwlabel and regionprops function measure binary image of the target object attributes.)