IDl

图像时频变换实例，包括FFT变换、FFT逆变换、DCT变换、DCT逆变换、DWT变换、DWT逆变换、WHT变换、WHT逆变换等。(Examples of image frequency conversion, including FFT transform, FFT transform, DCT transform, DCT transform, DWT transform, DWT transform, WHT transform, inverse transform, etc..)

ImageMagick® is a software suite to create, edit, compose, or convert bitmap images. It can read and write images in a variety of formats (over 100) including DPX, EXR, GIF, JPEG, JPEG-2000, PDF, PhotoCD, PNG, Postscript, SVG, and TIFF. Use ImageMagick to resize, flip, mirror, rotate, distort, shear and transform images, adjust image colors, apply various special effects, or draw text, lines, polygons, ellipses and Bézier curves.

产生运动模糊图像以及逆滤波，维纳滤波的恢复效果比较(Produce motion-blurred images, as well as inverse filtering, Wiener filtering effect of the restoration of)

k-均值聚类算法实现灰度图像分割，输入图像矩阵和聚类中心个数，返回为最终的聚类中心和图像中每个像素所属类的编号（对应于图像矩阵）(k-means clustering algorithm to achieve gray-scale image segmentation, the input image matrix and the number of cluster centers, the return for the final image of the cluster centers and their respective categories in each pixel number (corresponding to the image matrix))

双目匹配计算视差，生成深度图。（前提是用自己标定好的摄像头拍的图片，导入内外参数然后进行立体匹配）(Binocular matching calculates parallax and generates depth map.(The premise is to take a picture with your own calibrated camera, import internal and external parameters, and then stereo matching))

1、可制作圆形、椭圆形、菱形、方形、三角形印章。 2、支持多种特效：翻转图形、透明处理、高斯模糊、亮度/对比度/饱和度/锐化/反相/海绵/陨化(磨砂)/浮雕等等。 3、可将制作好的印章保存至印章库。 4、支持1％－1000％比例缩放。 5、支持导出印章图片(透明图章使用GIF格式)。 6、支持预览/打印。(1, can be made round, oval, diamond, square, triangular seal. 2, supports a wide range of effects: flip graphics, transparent deal, Gaussian blur, brightness/contrast/Saturation/Sharpness/RP/sponge/meteorite of (Matte)/relief and so on. 3, can be saved to create a good seal of the Treasury seal. 4, in support of 1-1000 scaling. 5, support for export seal picture (stamp the use of transparent GIF format). 6, support for preview/print.)

cvpr2012_oral On Multiple Foreground Cosegmentation(In this paper, we address a challenging image segmentation problem called multiple foreground cosegmentation (MFC), which concerns a realistic scenario in general Webuser photo sets where a finite number of K foregrounds of interest repeatedly occur over the entire photo set, but only an unknown subset of them is presented in each image. This contrasts the classical cosegmentation problem dealt with by most existing algorithms, which assume a much simpler but less realistic setting where the same set of foregrounds recurs in every image. We propose a novel optimization method for MFC, which makes no assumption on foreground configurations and does not suffer from the aforementioned limitation, while still leverages all the benefits of having co-occurring or (partially) recurring contents across images. Our method builds on an iterative scheme that alternates between a foreground modeling module and a region assignment module, both highly efficient and scalable. In part)

基于小波变换的图像修复算法，对比了FDM和TV算法。(Image restoration algorithm based on wavelet transform)

基于模糊对比度的图像增强方法，大致过程仍然是先把图像从空间域映射到模糊域，在模糊域内通过定义一个局部对比度算子，然后通过对凸函数的加强来放大像素邻域的各像素之间的差异。 (Based on the fuzzy contrast image enhancement method, the general process is still the first images from space domain is mapped to the fuzzy field in fuzzy field through the define a local contrast operator, and then the convex function to enlarge the strengthening of pixels each neighborhood pixel differences. )

遗传算法与BP神经网络结合，可以进行彩色图像和灰度图像的分割。(Genetic algorithm and BP neural networks that can be color images and gray-scale image segmentation.)