Image-Similar

运用边缘检测算子，采用不同结构元素并结合形态学对边缘图像进行边缘检测。(Using edge detection operator, and combine elements of different morphological structures on the edge of the image edge detection.)

sar图像的基于R-D模型的几何纠正，主要是利用RD模型的数学公式进行相关的几何纠正(Geometric rectification based on RD model of SAR)

对图像进行处理，包括加遮挡，旋转，仿射变换，形状调整等等。(Image processing, including plus occlusion, rotation, affine transformation, the shape of the adjustment.)

消除波面倾斜的函数，可以用于将波面的倾斜消去(Elimination wavefront tilt function, can be used to eliminate the inclined wavefront)

本程序可以实现MPEG-2I帧基本层编码和解码。图像大小为352*288.(This program implements the MPEG-2 I base layer frame encoding and decoding. Image size is 352* 288.)

图像处理模式识别一种分类算法：svm，对于所提取的图像的特征进行训练学习然后分类。(Image processing, pattern recognition of a classification algorithm: SVM trained to learn the characteristics of the extracted image and then classified.)

一篇关于总结了行为识别各种资源的论文，涵盖了通常的数据集、兴趣点检测，特征提取的方法以及识别检测的算法(A paper that summarizes the various resources of behavior recognition, covering the normal data set, the interest point detection, feature extraction methods and the identification detection algorithm)

在数字图像处理中.应用MATLAB对图像进行区域处理(In digital image processing. Application of MATLAB to deal with images of regional)

基于多帧图像插值（Interpolation）技术的方法是SR恢复技术当中最直观 的方法。这类方法首先估计各帧图像之间的相对运动信息，获得HR图像在非均 匀间距采样点上的象素值，接着通过非均匀插值得到HR栅格上的象素值，最后 采用图像恢复技术来去除模糊和降低噪声（运动估计!非均匀插值!去模糊和 噪声）。(In this paper, we propose a novel method for solv- ing single-image super-resolution problems. Given a low-resolution image as input, we recover its high- resolution counterpart using a set of training exam- ples. While this formulation resembles other learning- based methods for super-resolution, our method has been inspired by recent manifold learning methods, par- ticularly locally linear embedding (LLE). Speci?cally, small image patches in the low- and high-resolution images form manifolds with similar local geometry in two distinct feature spaces. As in LLE, local geometry is characterized by how a feature vector correspond- ing to a patch can be reconstructed by its neighbors in the feature space. Besides using the training image pairs to estimate the high-resolution embedding, we also enforce local compatibility and smoothness con- straints between patches in the target high-resolution image through overlapping. Experiments show that our method is very ?exible )

可以快速准确的找出光斑、或者任何椭圆形状二值图像的质心(The center of mass of a two value image can be quickly and accurately identified.)