TV_resto

合成孔径雷达（SAR）成像的距离徙动校正(Synthetic aperture radar (SAR) imaging distance migration correction)

图像预处理的过程彩色图像去噪，彩色图像增强，彩色图像锐化(Image pre-process color image denoising, color image enhancement, color image sharpening)

基于MATLAB实现图像融合，左右焦距融合(Image fusion based on MATLAB,Left and right focal length fusion)

用halcon给实际采集的图像进行畸变矫正，然后可以再人为添加一定程度的畸变，以便于定量研究，可运行已调试，可作为学习参考(Halcon is used to correct the distortion of the image collected, and then the human can add some degree of distortion to facilitate quantitative research. It can be run and debugged, and can be used as a reference for study)

说明：  水体提取功能，里面主要实现了多源遥感卫星水体提取，入库，推送等后续代码功能(Water extraction function, which mainly realizes the multi-source remote sensing satellite water extraction, storage, push and other follow-up code functions)

用于图像融和的窗口化工具，包含了几乎所有的常用融和算法：pca, Ihs, 金子塔,小波变换，多孔小波变换，brovey融合等。(The window for image integration tools, including almost all of the commonly used integration algorithm: pca, Ihs, pyramid, wavelet transform, multi-Kong Xiaobo transformation, brovey integration.)

压缩感知重构算法--固定点延拓法，用于大规格图像重构处理(Compressed sensing reconstruction algorithm- a fixed point continuation method for large size image reconstruction process)

采用基于LSB的随机图像隐藏技术实现将一幅图像（目标图像）隐藏到另一幅图像（载体图像）中。包含目标图像yctx.bmp，载体图像Miss.bmp，图像隐藏代码randlsbimghide.m文件，图像读取代码randlsbimgget.m文件，随机位选择代码randinterval.m文件。(LSB-based technique of random images to achieve a hidden image (object image) to another piece of hidden images (vector image) in the. Includes target image yctx.bmp, vector image Miss.bmp, image hidden code randlsbimghide.m file, image file reading code randlsbimgget.m, random bits select the code randinterval.m file.)

利用Hough变换，可以检测图像中的多条线段，效果很好(using hough transform for line detection)

为了提高数字图像中椭圆检测的效率和准确性,提出了一个基于最小二乘法的改进的随机椭圆检测算法. 该算法随机选取图像中的3 个边缘点,在以这3 个点为中心的窗口内,从边缘点中拟合出可能椭圆,并通过随机选 取的第4 个边缘点来确认可能椭圆. 利用直接最小二乘法椭圆拟合的特性,引入可能椭圆边缘点收集和椭圆重新 拟合的迭代过程来提取最终的椭圆参数. 通过对含有不同噪声的仿真图片和包括残缺椭圆的实际图片的实验表 明,新算法的改进是有效的. 与原算法相比,新算法降低了对参数的依赖性,提高了检测的速度、稳定性和准确性, 同时保留了原算法的抗噪声能力.(: An imp roved randomized ellip se detection algorit hm based on least square approach was proposed to enhance t he efficiency and accuracy of ellip se detection in digital images. This algorit hm randomly se2 lect s three edge point s in t he image , and t hen uses least square approach to fit all t he edge point s in three windows , which are defined by t he t hree edge point s. The forth edge point is randomly selected to judge whet her a possible ellip se exist s in t he image. Utilizing the characteristic of direct least square fit ting of ellip se , an iteration process of edge point collecting and ellip se refit ting of possible ellip se was int roduced to ext ract t he final ellip se’s parameters. Artificial images wit h different level s of noise and nature images containing incomplete ellip ses were employed to test t his algorithm. Experimental result s show that t he improvement s are notable. Compared with the original algorit hm , t he propo sed algorit hm reduces)