tiduxiajiang

一个很有用的SAR图片，可用于SAR图像的目标识别(A very useful SAR image can be used for target recognition SAR image)

深度图像处理,主要的是对深度图像进行区域分割(depth map)

这段代码的功能是实现图像去雾处理，Matlab代码，可以直接运行的(Functionality of the code is to realize image processing demisters Matlab code can be run directly)

说明：  提取图像的hu矩 使用matlab编写 相当稳定 计算速度较快(image hu moment steadily run fast very good worth trying)

对图片预处理加入高斯噪声，各种经典边缘检测算子对图像进行边缘提取(Gaussian noise on the image pre-processing, a variety of classic edge detection operator to extract image edge)

求一个图像的最大内接矩形面积。 步骤： 1.相机标定。首先根据物像关系式求出其中的参数。注意参数求出后要进行参数校验。 2.从背景中分离出目标 3.边缘检测 4.目标形状参数计算。(For an image of the largest inscribed rectangle area. Steps: 1. Camera calibration. First of all object-image relationship in accordance with the parameters obtained. Attention to the parameters obtained after parameter calibration. 2. From the context of isolated target 3. Edge detection 4. Target shape parameters.)

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

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)

说明：  QR二维码识别中在对图像预处理后最重要的一步就是要进行定位，QR二维码中有三个位置探测图形，通过扫描其特征便可以进行精细定位，提出了一种新的算法用于筛选候选点。(In QR code recognition, the most important step after image preprocessing is to locate. There are three position detection patterns in QR code, which can be precisely located by scanning its features. A new algorithm is proposed to screen candidate points.)

说明：  图像增强的目标是改进图片的质量，例如增加对比度，去掉模糊和噪声，修正几何畸变等；图像复原是在假定已知模糊或噪声的模型时，试图估计原图像的一种技术。 图像增强按所用方法可分成频率域法和空间域法。前者把图像看成一种二维信号，对其进行基于二维傅里叶变换的信号增强。采用低通滤波（即只让低频信号通过）法，可去掉图中的噪声；采用高通滤波法，则可增强边缘等高频信号，使模糊的图片变得清晰。具有代表性的空间域算法有局部求平均值法和中值滤波（取局部邻域中的中间像素值）法等，它们可用于去除或减弱噪声。 (A sharp and clear image is not directly produced from the optics, however, digital signal processing applied to the sampled image produces a sharp and clear final image that is also insensitive to misfocus related aberrations. This paper gives an overview of Wavefront Coding and example images related to the two applications of machine vision/label reading and biometric imaging. Design techniques of Wavefront Coding are unique from that of traditional imaging system design since both the optics and digital processing characteristics of the system are jointly optimized for optimum system performance.)