curves-movement-by-level-set-method

这是一个matlab环境下的关于图像频谱分析的源代码，内附图像。(This is a Matlab environment on the image spectrum analysis of source code, containing images.)

说明：  合成孔径雷达点目标仿真，线性变标算法（CSA），注释完整，可以直接运行，信号模型参考书目《合成孔径雷达成像算法与实现》。(Synthetic aperture radar point target simulation, linear scaling algorithm (CSA), complete annotations, can be run directly, the signal model reference bibliography "Synthetic aperture radar imaging algorithm and implementation".)

图像质量评价经典算法，ssim算法评价图像质量好坏程度的度量(Image quality assessment of the classical algorithm, SSIM algorithm.A measure of the degree of image quality )

一个盲去卷积程序，可以实现去除图像的各类模糊，同时可进行相关参数的自适应调整。(A blind deconvolution process can be achieved to remove all kinds of image blur, while the relevant parameters can be adaptive.)

基于灰度图像处理的LSB密写的实现算法，matlab编程实现(Based on gray-scale image processing of LSB Steganography algorithm, matlab Programming)

bode图，可以实现如何绘制bode图的过程和详细步骤。(Bode figure, can realize how to draw the process and detailed bode figure steps )

此程序用于画混沌系统的相图及其分叉图，使用时只需要写出相应的混沌微分方程，便可画出相应的图(This procedure for drawing the phase diagram of chaotic systems and its Poincare section, when used only need to write the corresponding chaotic differential equations, will be able to draw the corresponding graph.)

二值图像处理运算是从数学形态学下的集合论方法发展起来的,尽管它的基本运算很简单，但是却可以产生复杂的效果。常用的二值图像处理操作有许多方法，如腐蚀、膨胀、细化、开运算和闭运算等等。本文对这些内容作些研究探讨， 希望对爱好图像处理的朋友有所帮助。(Binary image processing algorithms are developed set theory in mathematical morphology. Although its basic operation is simple, it can produce complex effects. Commonly used binary image processing operations there are many ways, such as corrosion, expansion, refinement, open operation and closed operation and so on. In this paper, some of these studies to explore, I hope to love image processing friends help.)

通过数字图像相关的方法计算两幅图像之间的位移，计算时间较长，是最基础的DIC，没有优化。(Digital image correlation method to calculate the displacement between the two images, the time is longer, is the most basic DIC, no optimization.)

DCT在图像重构，压缩感知以及稀疏表示中的应用(DCT in image reconstruction, compressed sensing and sparse representation of the application)