MRF-ENCH

《智能图像处理技术》——由李弼程等编写，区别于大多传统的图像处理技术书籍，该书主要讨论了图像处理的最新发展，如图像的特征分析、配准、融合、分类等技术，具有前沿性和先进性( Intelligent image processing technology - such as prepared by Bicheng, mostly from the traditional image processing technology books, the book discusses the latest developments in image processing, such as the characteristics of image analysis, registration, integration, classification and other technology, having cutting-edge and advanced)

人耳识别，包含图像预处理，图像特征点的提取，比较实用(Ear recognition)

这MFC图像处理源代码总集包括了均值滤波，直方图均衡，高斯平滑，，锐化，拉普拉斯锐化（边缘检测），阈值变(With the MFC implementation of an image processing example code)

用kinect获取3D图像，并从3D图像中用OpenCV方法从深度图中获取梯度边缘，从而得到更多信息，做后续处理(Get with kinect 3D images, and get the edge gradient from the depth map from a 3D image using OpenCV method to obtain more information, do follow-up treatment)

这个是用matlab编写的读取遥感图像envi的程序(This is prepared using matlab to read the procedures for remote sensing image envi)

用matlab对图像进行锐化，加噪，滤波，平滑滤波，中值滤波等处理(Matlab is used to sharpen the image, add noise, filter, smooth filter, median filter and so on)

说明：  合成孔径雷达点目标仿真，线性变标算法（CSA），注释完整，可以直接运行，信号模型参考书目《合成孔径雷达成像算法与实现》。(Synthetic aperture radar point target simulation, linear scaling algorithm (CSA), complete annotations, can be run directly, the signal model reference bibliography "Synthetic aperture radar imaging algorithm and implementation".)

This program is able obtain the cemtral point of a template in an image.The program gives 4 output images performing diferent kind of filtering, and giving the center of the matchig template.

这是通过径向偏振贝塞尔高斯光束聚焦一个组合 二进制相光学元件和高数值孔径的镜头。(This is achieved by focusing a radially polarized Bessel–Gaussian beam with a combination of a binary-phase optical element and a high-numerical-aperture lens.)

提出了一种基于图像边缘连接的线段检测方法。数字图像中的线段是由很多线段图元组成,在同一 条线段中,它们的方向是相同的并且受到真实线段的方向约束。因此可以通过提取小的线段图元, 然后分析它们 的连接特性, 进行线段的检测。首先用ADM 算法对图像进行边缘检测, 得到单像素宽的边缘 然后在4 个方向上 进行线段的检测 对初步得到的结果进行合并和验证, 去掉短的线段, 连接临近的线段。经过实验证明, 该方法能 够快速地提取图像中的线段,并且对噪声具有一定的鲁棒性(A line segment connecting a detection method based on image edges. The segment of the digital image is composed by many segments elements, their orientation is the same and by the real line segment direction constraint in the same segment. By extracting a small segment Element can then analyze their connection characteristics for the detection of the line segment. First with ADM algorithm for edge detection on the image to obtain a single-pixel-wide edge then in the four directions on the detection of the line segments merger and verification of the preliminary results obtained, removing the short line segments, the line segments connected near. The experiments show that this method can quickly extract the line segments in the image, and certain robustness to noise)