svt

在matlab中实现透视变换。算法正确高效，这种仿射变换经过修改后可用于图像矫正或者摄像机标定等用途。(Matlab in perspective transformation. Correct and efficient algorithm modified this affine transformation can be used to image correction or camera calibration purposes.)

说明：  针对相机标准线扩散函数的IDL测试源码，用于相机图像质量评估(IDL test source code for the standard line spread function of the camera, used for camera image quality assessment)

以实例列举了MATLAB中常用的图像处理函数的代码(Examples are given to illustrate the image processing functions commonly used in MATLAB code)

说明：  LBP是一种用来描述图像局部纹理特征的算子；它具有旋转不变性和灰度不变性等显著的优点。(LBP is an operator used to describe local texture features of images; it has significant advantages such as rotation invariance and gray invariance.)

这是一个基于vc++语言下读取像素点灰度值(write highhui of a photo!)

手指静脉预处理，图像分割，静脉纹路分割，滤波去噪，细化等相关代码(Finger vein pretreatment, image segmentation, vein segmentation, filtering and denoising, thinning and other related codes)

说明：  基于MATLAB的条形码识别。带GUI可视化用户操作界面。读取条形码，经过一系列预处理，如灰度化，去噪，直方图增强，中值滤波，二值化，腐蚀，识别等。可识别20多张条形码图片，另外可定制二维码的识别，二维码可自定义生成内容，生成二维码，然后嵌入数字水印进行加密传输，接收方提取水印的二维码，识别。(Bar code recognition based on MATLAB. Visual user interface with GUI. Read bar code, after a series of preprocessing, such as graying, denoising, histogram enhancement, median filtering, binarization, corrosion, recognition and so on. It can identify more than 20 bar code images, and can customize the identification of two-dimensional code. The two-dimensional code can generate the content of the two-dimensional code, generate the two-dimensional code, and then embed the digital watermark for encryption transmission. The receiver can extract the two-dimensional code of the watermark for identification.)

说明：  MATLAB实现基于互相关的亚像素级图像配准源代码,MATLAB_Image_subpixel_Mutual_info(MATLAB-based cross-correlation of sub-pixel image registration source code, MATLAB_Image_subpixel_Mutual_info)

粒子滤波与PHD多目标跟踪比较，三目标分别进行粒子滤波和marginalPHD滤波跟踪比较结果。(PHD particle filter multi-target tracking compared with the three goals were to filter tracking particle filter and marginalPHD comparison.)

图像修复是对图像中破损区域进行信息填充，以减少图像破损所带来的信息损失的过程。 传统的图像修复方法需要依赖图像的具体结构来制定相应的修复方法，压缩感知理论的提出，使得可以利 用信号的稀疏性来对图像进行修复。基于K 奇异值分解（KSVD）与形态学成分分析（MCA，Morphological Component Analysis）的图像修复方法首先采用形态学成分分析方法对破损图像进行特征分析，将其分解 为结构部分和纹理部分；然后基于学习型字典KSVD分别对这两部分进行过完备字典训练；最后利用训练得 到的字典实现对破损图像的修复。相比于传统的图像修复方法，该方法具有适应性强、修复效果好等优点(Image inpainting is to fill the missing data in corrupted images and thus to reduce the information loss of damaged image. Traditional inpainting algorithms are dependent on specific structure of target images compressive sensing theory makes is possible to realized image inpainting with signal sparsity. This paper proposes a novel inpainting algorithm based on KSVD and MCA algorithm, which first decomposes the image into texture part and structure part, and then trains the two dictionaries for these two parts with KSVD and reconstructs the original image with these two trained dictionaries. Experiment indicates that the proposed algorithm is of better adaptability and performance as compared with traditional algorithms.)