LiaoThreshold

图像的逆滤波 维纳滤波 同时可以对图像进行模糊处理比如运动模糊 卷积模糊(Using C++ to complete images of conversion, processing and compression process, is to learn good reference digital image processing program!)

中南大学数字图像处理上机实验指导书及参考答案，全部由本人编写，在MATLAB 6.5上运行通过。包括图像变换及频域滤波，空间域图像增强，图像边缘检测及参考图片，比网上流传的好的多，是学习图像处理的基础。(Zhongnan University of digital image processing on the experimental guide and reference book answers all prepared by me, MATLAB 6.5 to run through. Image Transform and including the frequency domain filtering and spatial domain image enhancement, edge detection and reference photographs, spread over the Internet much more study is the basis of image processing.)

利用Zernike方法对圆形标志点中心进行提取(The circular mark center is extracted by Zernike method.)

对BMP文件进行图像处理，包括：边缘检测、频域变换、几何变换、图像变换校正、灰度变换、图像编码、平滑和匹配(BMP files for image processing, comprising: an edge detection, a frequency domain transformation, geometric transformation, image transformation correction gradation conversion, image coding, and matching the smooth)

基于MATLAB的图像处理源程序集，包括阈值、二值化、灰度变化，边缘提取等等(MATLAB based image processing source code set, including threshold, binary, gray scale, edge extraction, etc.)

说明：  主要颜色谱 计算主要的颜色来舍弃其他的颜色，用少数的颜色个数代替大多数进行聚类(Main color spectrum calculation primary colors to abandon other colors)

可用于视频目标检测中背景生成的混合高斯模型(Can be used for video object detection in the context of generating a mixture of Gaussian model)

用差分盒维数处理图像，通过对图像分块，然后每一块来计算该区域的分维数，将其作为该区域所有像素上每一像素的分维数。然后，增强分维数分布图效果，然后取阈值，最后，给人造目标加框。(Differential box counting process the image, the image block, and then every one to calculate the fractal dimension of the region, as all the pixels in the region of each pixel on the fractal dimension. Then enhanced fractal dimension distribution effect, and then take the threshold, and finally, to the man-made objects framed.)

对嵌入水印的图象进行不同的攻击 添加噪音，滤波，剪切，压缩，旋转45度(Watermark on the images embedded in a different attack to add noise, filter, shear, compression, rotating 45 degrees)

说明：  Hu不变矩的的一至七个矩的代码以及论文。matalb版本，可直接用。(Matlab Code of Hu Moment Invariant)