ImageTrans

针对最低有效位 LSB方法保密性较差的问题, 本文提出了一种复合Henon混沌序列和LSB的图像加密解密算法(For the least significant bit LSB method less confidentiality issues, this paper proposes a complex Henon chaotic sequence and the LSB of the image encryption and decryption algorithm)

crimini算法对图形进行修复，您能够充分的利用空间信息，纹理信息(crimini graph algorithm to repair, you can take full advantage of the spatial information, texture information)

有较好的参考价值，进行波形数据分析,实现六自由度运动学逆解算法。( There are good reference value, Waveform data analysis, Six degrees of freedom to achieve inverse kinematics algorithm.)

本文主要是针对传统混合高斯模型运动目标检测算法的不足做出了一些改进(This article is for the shortcomings of traditional Gaussian mixture model moving object detection algorithm made some improvements)

超高斯光束在自由空间中的衍射传播，利用角谱理论。(Super-Gaussian beam diffraction propagation in free space, the use of the angular spectrum theory.)

truncated DCT. good for video compression.

一个图片浏览器程序，除了基本的图片浏览功能外，还包括图像特效处理功能和特效处理算法。(An image browser program, in addition to basic image browsing functions, including image effects processing capabilities and effects-processing algorithms.)

说明：  这是“An efficientlocalChan–Vesemodelforimagesegmentation”（简称LCV模型）的MATLAB源代码。LCV模型是非常重要局部区域活动轮廓模型，它被广泛使用于各个领域，如MRI大脑图像分割，血管图像分割，图像偏差场纠正。(This is "An efficientlocalChan-Vesemodelforimagesegmentation" (referred to as the LCV model) of the MATLAB source code. LCV model is very important to local area active contour model, which is widely used in various fields, such as MRI brain image segmentation, vessel segmentation, image bias field correction.)

说明：  level set方法中的经典模型cv模型的matlab的源程序 (level set method of classical model cv model of the source Matlab)

说明：  在这个知识库中，图形信号处理的一些有趣的特性被表示出来。演示通过经典信号处理和图形信号处理对一维和二维欧几里得域信号应用低通滤波器，比较两种方法的结果。在此基础上，验证了图形信号处理的工作机制。此外，还描述了在非欧几里得域上滤波信号的示例。(In this repository, Some fascinating features of Graph Signal Processing were represented. Demos incudes applying a low-pass filter on both 1D and 2D euclidian domain signal by classical signal processing and also Graph signal processing to compare both results are the same. Within that way, we will validate the working mechanism of Graph Signal Processing. In addition to this, an example of filtering a signal on the non-euclidian domain was also represented.)