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LSB替换隐写
说明： LSB(英文 least significant bit)即最低有效位。LSB加密是信息隐藏中最基本的方法。由于人们识别声音或图片的能力有限，因此我们稍微改动信息的某一位是不会影响我们识别声音或图片的。(LSB replace steganography)
- 2021-04-20 11:48:50下载
- 积分：1
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C_graphics.h
C语言图形、图像函数 功能实用全面介绍(C language graphics, images, full function functional and practical introduction)
- 2010-05-06 14:20:15下载
- 积分：1
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Smooth
对图像进行平滑处理，像各种滤波的方法，如均值滤波法、中值滤波法(Smoothing the image, like the various filtering methods, such as mean filtering, median filtering method)
- 2010-07-16 13:17:31下载
- 积分：1
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AutomaticImageDeWeatheringUsingCurveletBasedanishi
说明： 用曲波变换点边缘检测实现自动恢复受天气影响的图像(Qu Bo transformation point with edge detection for automatic restoration of images affected by the adverse weather)
- 2008-11-17 14:02:07下载
- 积分：1
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NcutImage_7
很好的图像分割软件，内有全部源码，对研究matlab图像识别处理很有帮助(good image segmentation software, comprising all the source code, the study Matlab image recognition processing helpful)
- 2007-06-20 16:29:56下载
- 积分：1
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ICP-point-cloud-registration
三维激光点云配准是点云三维建模的关键问题之一。经典的 ICP 算法对点云初始位置要求较高且配准
效率较低，提出了一种改进的 ICP 点云配准算法。该算法首先利用主成分分析法实现点云的初始配准，获得较好
的点云初始位置，然后在经典 ICP 算法的基础上，采用 k － d tree 结构实现加速搜索，并利用方向向量夹角阈值去除
错误点对，提高算法的效率。实验表明，本算法流程在保证配准精度的前提下，显著提高了配准效率。
(Three-dimensional laser point cloud registration is one of the key three-dimensional point cloud model. High classical ICP algorithm to the initial position of the point cloud registration requirements and low efficiency, proposed an improved ICP point cloud registration algorithm. Firstly, the use of principal component analysis of the initial point cloud registration, get a better initial position of the point cloud, then the basis of classical ICP algorithm using k- d tree structure to achieve speed up the search, and using the direction vector angle the removal of the threshold point error and improve the efficiency of the algorithm. Experiments show that the algorithm processes to ensure the accuracy of registration under the premise, significantly improve the efficiency of registration.)
- 2016-08-01 10:34:57下载
- 积分：1
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THEPROBABILITYH-THEVIDENCEFUSION
针对杂波环境下的多个机动目标跟踪问题, 本文将多模型概率假设密度 (Multiple-model probability hypothesis
density, MM-PHD) 滤波器和平滑算法相结合, 提出了 MM-PHD 前向 – 后向平滑器. 为了避免引入复杂的随机有限集
(Random finite set, RFS) 理论, 本文根据 PHD 的物理空间 (Physical space) 描述法推导得到了 MM-PHD 平滑器的后向更
新公式. 由于 MM-PHD 前向–后向平滑器的递推公式中包含有多个积分(By integrating the multiple-model probability hypothesis density (MM-PHD) filter with the smoothing al-
gorithms, an MM-PHD forward-backward smoother is proposed in this paper for tracking multiple maneuvering targets
in clutter. To avoid use of complex random finite set (RFS) theory, the backward updated equation of the MM-PHD
smoother can be derived according to the physical-space explanation of the PHD)
- 2013-09-23 15:36:28下载
- 积分：1
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kalmanfilter(1)
典型的一维kalman滤波原理程序，容易掌握！(typical one-dimensional Kalman filtering process easy!)
- 2007-06-17 17:11:43下载
- 积分：1
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matlab
zemax非序列下gaussian光束的matlab程序（包括zemax演示源文件）(zemax sequence under non-gaussian beam matlab program (including zemax demo source files))
- 2013-09-25 15:25:18下载
- 积分：1
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gaussianba
使用特征差别提取，通过特征差别相减，以去除高斯背景(Using the characteristics of different extraction, the characteristics of different background subtraction, to remove Gauss)
- 2014-01-07 17:31:17下载
- 积分：1
