sar-edge-detection

Adaptive Perona–Malik Model Based on the Variable Exponent for Image DenoisingThis paper introduces a class of adaptivePerona–Malik (PM) diffusion, which combines the PM

直方图的计算与显示分析图像、物体和视频信息过程，我们常把看到的物体用直方图（histogram）表示，直方图可以用来描述各种不同的事情，如物体的色彩分布、物体边缘梯度模板，以及表示目标位置的概率分布(Calculation and analysis of the histogram display images, objects and video information process, we often see objects with the histogram (histogram) indicates, the histogram can be used to describe a variety of different things, such as the color distribution of objects, object edges gradient templates, and the probability distribution of the target position)

用于Landsat5 TM数据的辐射定标(Calibration for Landsat TM data using IDL)

说明：  这是一个图像配准的MATLAB代码，有很好的GUI界面，以像素级进行配准。(The image matching MATLAB code is based on pixel with a good GHI.)

亮度代表了图像的明暗程度，颜色代表了图像的色度，它包含了色调和饱和度。这个代码可以自动对这三个参数进行调整。(Brightness represents the degree of image brightness, color represents the color image, which includes hue and saturation. This code can be automatically adjusted to the three parameters.)

ROF-L2去噪模型，可以有效的去除加性噪声(ROF-L2 denoising model)

对256bmp进行图象处理 对256bmp进行图象处理(256bmp carried out on the image processing carried out on 256bmp image processing)

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)

使用QT编程实现2D图像处理的各功能，包括彩色图转灰度、二值化、二值的形态学操作、灰度的形态学操作等等。(Using QT programming each 2D image processing functions, including color conversion grayscale, binary, binary morphological operations, grayscale morphological operations and so on.)

基于霍夫变换的直线检测，效果非常好，图片自己找，可能需要对图片格式做操作。(Line Detection Based on Hough Transform)