minboundrect

图像处理基本算法其中之一的yuzhibianhua (Image processing one of the basic algorithm yuzhibianhua)

说明：  在ENVI中利用此程序可将多光谱影像拆分为单个波段。(In ENVI, multi-spectral images can be divided into single bands by using this program.)

分割视图 希望大家多多批评指正 多多交流(segmentation View I hope Members can interact more criticism correction)

区域邻接图的合并规则，在进行区域合并时可以使用，希望对大家有用(region merging for region adjecent gragh，might it be help for you.)

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.)

这个是图像处理中的hough变换的C++源代码，工需要的同学参考学习。(This is the image processing hough transform C++ source code, engineering students need to learn.)

在图像的DCT系数上嵌入信息，图像为常见的512*512大小的灰度图（实验所用图像为LENA.BMP）。嵌入的信息为一二进制Logo图（实验所用logo图为tj-logo.bmp），该图大小为32*32，共1024个Bit。 1. 在LENA图中嵌入水印，输出嵌入后的水印图像。 2. 对水印图像解码，输出解码后得到的logo图，并统计错误率。 3. 使用不同的嵌入强度进行嵌入，观察其对作品直觉效果和解码效果的影响，绘制相应的曲线。 4. 使用加入噪声、改变对比度、JPEG压缩等攻击方法对水印作品进行攻击，查看解码的效果。 (Information embedded in the DCT coefficients of the image, the image of the common 512* 512 size gray-scale (experimental image LENA.BMP). Information embedded in a binary Logo Figure (used in the experiment logo picture shows the tj-logo.bmp), the plot size 32* 32, 1024 Bit. LENA Figure embedded watermark, the watermark image output embedded. (2) logo watermark image decoding, the output decoded Figure statistical error rate. (3) using a different embedding strength for embedding, observe the works intuitive effects and decoding results, and draw the corresponding curve. (4) by adding the noise, change the contrast, JPEG compression attack methods to attack, to see the effect of decoding the watermark works.)

为图像添加各种噪声，如高斯噪声、泊松噪声、椒盐噪声等。（需有openCV）(Add all kinds of noise for the image, such as Gaussian noise, Poisson noise, salt and pepper noise. (The need for openCV))

Real-time Specular Highlight Removal实现论文“Real-time Specular Highlight Removal Using Bilateral Filtering”中算法(Real-time Specular Highlight Removal Papers " Real-time Specular Highlight Removal Using Bilateral Filtering" in the algorithm)

说明：  实现混合高斯的功能，再次基础上可进行任意操作(The function of mixed Gaussian can be realized, and any operation can be carried out on the basis of it again.)