matlabprogram

说明：  阈值分割。基于二维直方图及混沌粒子群的图像分割方法(Thresholding. Based on two-dimensional histogram and chaotic particle swarm methods for image segmentation)

说明：   图形学编程，界面很漂亮，转载(graphics programming interface is very beautiful, reprinted)

windows下c++鱼眼校正，debug内exe可直接运行看结果。内附参考文献，更详细文献可见论文《超大广角畸变图像的校正和展开》。(C++ fisheye correction under windows, debug within exe can run directly to see the results. With reference to the literature, more detailed literature can be seen in the paper "super wide-angle distortion image correction and expansion".)

基于暗原色的雾天图像清晰化算法研究,系转载，如有雷同，概不负责(Algorithm based on the clear image of dark primary colors fog)

说明：  基于BoVW的图像特征提取，以及图像检索(Image feature extraction and image retrieval based on BoVW)

模式识别经典方法之一 K均值算法（KMeans）进行图像分割 有完善的图形界面 可以通过柱状图的形式动态展示聚类程序(One of the classical method of pattern recognition K means algorithm (KMeans) for image segmentation has improved graphical interface can be dynamically displayed in the form of histogram clustering procedure)

本算法有图像融合算法，聚类分析算法，去噪算法，运动模糊算法(This algorithm with image fusion algorithm, clustering analysis algorithm, the denoising algorithm, fuzzy algorithm)

卷积神经网络（Convolutional Neural Network）是一个专门针对图像识别问题设计的神经网络。它模仿人类识别图像的多层过程：瞳孔摄入像素；大脑皮层某些细胞初步处理，发现形状边缘、方向；抽象判定形状（如圆形、方形）；进一步抽象判定（如判断物体是气球）。(Convolutional neural network is a neural network specially designed for image recognition. It imitates the multi-layer process of human recognition image: pupil ingestion of pixels; some cells in the cerebral cortex preliminary processing to find shape edges and directions; Abstract judgment of shape (such as circles and squares); and further Abstract judgment (such as judging objects are balloons).)

多边形的合并算法，该算法能够实现任意两个多边形（包括凹多边形）的合并.( The polygon merge algorithm, this algorithm can realize wilfully two polygons (including concave polygon) merge )

对于遥感图像，研究了一种基于基于Contourlet变换和分形压缩方法，方法具有一定的实用价值，程序包中有实验图片。(For the remote sensing images, a kind of transformation based on Contourlet and fractal based compression methods, the method has some practical value, experimental pictures in the package.)