inverhuifu

本篇论文主要介绍地基云的自动检测！采用阈值分割！(This paper describes the automatic detection of the foundation of cloud! Using thresholding!)

通过对彩色图像的处理，来计算某一个区域的面积。(The color image processing to calculate the area of ​ ​ a region.)

图像去雾c++版源代码，实现效果还不错，可直接运行。(Fog to remove the c++ version of the source code, the effect is not bad, can be run directly.)

CVPR2013中出现的一种显著性特征检测算法，该算法用于模拟人眼视觉识别过程，提取图像中的显著性特征借后期目标对象的检测跟踪等使用，该算法(Context-Aware Saliency Detection。matlab implementation of an classical saliency detection alrogithm,which imitate our recognition process of eyes)

说明：  傅里叶谱与频域低通滤波 (a)从图书网站下载图4.41(a)并计算其(居中)傅里叶谱。(b)显示频谱。(c)在等式(4.8-7)中实现高斯低通滤波器。您必须能够指定结果2D函数的大小，M x N。此外，您必须能够指定高斯函数的中心位置。(d)从图书网站下载图4.41(a)，并对其进行低通滤波，以复制图4.48中的结果。(Fourier Spectrum and Lowpass Filtering in Frequency Domain (a) Download Fig. 4.41(a) from the book web site and compute its (centered) Fourier spectrum. (b) Display the spectrum. (c) Implement the Gaussian lowpass filter in Eq. (4.8-7). You must be able to specify the size, M x N, of the resulting 2D function. In addition, you must be able to specify the location of the center of the Gaussian function. (d) Download Fig. 4.41(a) from the book web site and lowpass filter it to duplicate the results in Fig. 4.48.)

基于马尔科夫随机场的，例子学习超分辨率复原代码。(This is an implementation of the example-based super-resolution algorithm. Although the applications of MSFs have now extended beyond example-based super resolution and texture synthesis, it is still of great value to revisit this problem, especially to share the source code and examplar images with the research community. We hope that this software package can help to understand Markov random fields for low-level vision, and to create benchmark for super-resolution algorithms.)

hit-miss方法下的图像骨架提取，很好用(hit-miss method of image skeleton extraction, very good use)

1.设计一个程序，对一幅灰度图像的实现如下几何变换,1)放大为原图1.5倍 2)绕中心旋转30度(CW) 3)采用偏移量插值实现一个透视变换. 灰度差值用最近邻插值和双线性插值 2. 绘制一幅灰度图像的梯度幅度图像（三点法求梯度），针对梯度幅度图像合理的选择一个阈值（通过试验即可）将其二值化，以获得图像边缘检测图像。 ((1) design a program, a grayscale image as geometric transformation, zoom 1) for 1.5 times the original 2) around the center of rotation of 30 degrees (CW) 3) interpolation of the offset to achieve a perspective transformation.gray level difference between the nearest neighbor interpolation and bilinear interpolation (2) draw a grayscale image of the gradient magnitude image (three-point method seeking gradient), the gradient magnitude image is reasonable to select a threshold value (the test can be) the second value to the image edge detection image.)

KSVD算法的工具包，安装在matlab的相关路径下，可以直接调用。(KSVD algorithm Kit installed in the path of matlab can be called directly.)

说明：  一种基于直方图改进的FCM聚类水下图像分割算法 文献加matlab实现代码(Improved histogram based FCM clustering literature plus underwater image segmentation algorithm matlab code)