资源列表
opencv
- 基于meanshift的单目标跟踪算法实现 说明： 1. RGB颜色空间刨分，采用16*16*16的直方图 2. 目标模型和候选模型的概率密度计算公式参照上文 3. opencv版本运行：按P停止，截取目标，再按P，进行单目标跟踪-Meanshift based single target tracking algorithm Descr iption: 1. RGB color space plane points, using a histogram 16* 16* 16 2
Lesson05
- 基于 nehe opengl教程制作的简单漫游程序，可实现上下左右键控制前后左右移动，wasd实现上下左右旋转。-Based nehe opengl tutorial simple roaming, which enables the front left and right arrow keys to control movement, WASD achieve vertical and horizontal rotation.
test
- 此源代码是基于MATLAB的车牌定位程序，可以准确的定位车牌并找出车牌区。输出车牌区图像。-This source code is based on MATLAB license plate locator that can accurately locate the plate and identify the license plate area. Output image plate area.
ImageSearch
- 基于小波变换的纹理图像检索程序，对Brodatz标准纹理库中分割后的图像进行检索实验-Wavelet-based texture image retri procedures, image segmentation Brodatz standard texture library after the search experiment
Block-TVNLR
- Image Compressive Sensing Recovery via Collaborative Sparsity
dft
- 其中dft.m 是通过该程序同时输出图片1,2的R、G、B三通道的DFT正反变换图、相角图、幅度图，图片1,2的彩色DFT正反变换图以及DFT后图片1,2幅度相位信息置换后的彩色结果图。 dct.m是通过该程序显示“实验室用原图像”中的图片3的R、G、B三通道DCT正反变化对比图，变换系数图以及彩色DCT正反变换图。 compress.m是通过该程序输出图片3的保留n个DCT变换系数重构彩色结果图。需要说明的是其中决定保留系数个数n的mask矩阵需要手动更改。-Wherein
ALSB_Code
- Image Compressive Sensing Recovery Using Adaptively Learned Sparsifying Basis via L0 Minimization
SDPC_Code
- Spatially Directional Predictive Coding for Block-based Compressive Sensing of Natural Images
GSR_Code_Package_2.0
- Structural Group Sparse Representation for Image Compressive Sensing Recovery
ctsoft
- 基于轮廓波变换的图像软阈值去噪程序，并通过等效视数、斑点噪声指数进行评价-Image-based soft thresholding wavelet transform program outline and uated by ENL, speckle noise figure
cthard
- 基于轮廓波变换的图像硬阈值去噪程序，并通过等效视数、斑点噪声指数进行评价-Hard-based image thresholding wavelet transform program outline and uated by ENL, speckle noise figure
Dual_Dic_SR
- Group-based Sparse Representation for Image Restoration