搜索资源列表
imregister
- In computer vision, sets of data acquired by sampling the same scene or object at different times, or from different perspectives, will be in different coordinate systems. Image registration is the process of transforming the different sets of data
124
- A Chaotic Algorithm of Image Encryption Based on Dispersion Sampling
HaNguyen_thesis
- MULTISENSOR SIGNAL PROCESSING: THEORY AND ALGORITHMS FOR IMAGE-BASED RENDERING AND MULTICHANNEL SAMPLING
pianweifenfangcheng
- 对可压缩的信号可通过远低于Nyquist标准的方式进行采样数据，仍能够精确地恢复出原始信号，对图像处理具有重要意义。-On the compressible signals can be well below the Nyquist sampling data standard manner, is still able to accurately restore the original signal, the image processing is important.
ppt-triangel
- 本專題分為3大部份 1. 對單一圖片做邊緣檢測後, 統計其複雜度, 再以 Delaunay 三角網來分割複雜度較高的圖形, 將此圖形之三角網的三點座標與RGP值 取樣後壓縮儲存, 及達成壓縮目的. 還原部份為, 以線性內插則是將取樣後的三角網三點內插後還原之原理, 還原單一影像, 再將所有還原之影像串連撥放即完成之影片還原. 2.讀取RS-232接至RFID門禁系統, 讀取Myfair悠遊卡之卡號, 進行身份辨識後, 可選擇需要觀賞之影片.
Based-on-the-pump-performance-curve-skeleton-recov
- 一种基于骨架的水泵性能曲线复原方法---:考虑到编制水泵装置选型及优化方面软件须将大量复杂的水泵综合性能曲线图片数字化后输入计算机，提出了"扫描一细化一取样一拟合"的复原方法，较好地解决了扫描图片线条较粗影响精度、人工取样费时费力的问题.该方法在"水泵优化与选型"软件中得到成功应用.-Based on pump performance curve skeleton--- restoration method: taking into account the selection and prepa
multiple-channel-image-sampling-system
- multiple channel image sampling system
double-sampling
- CMOS图像传感器对数模式极其双采样技术，可实现对数模式下的噪声去除，国外博士论文-Logarithmic mode, the CMOS image sensor is extremely double sampling technique, can be realized on the number of mode noise removal
CS-of-multi-static-SAR
- 压缩感知在多基地合成孔径雷达中的应用，关于采样相关性与图像重建质量的关系分析-Compressed sensing applications in the multi-base synthetic aperture radar, relationship analysis on sampling correlation with the quality of image reconstruction
lossless-image-compression-based-on-optimal.pdf.z
- The optimal predictors of a lifting scheme in the general n-dimensional case are obtained and applied for the lossless compression of still images using rst quincunx sampling and then simple row-column sampling. In each case, the e ciency of the
Matching-Algorithm
- 要：图像匹配是计算机视觉中许多领域的基础，特征提取则是图像匹配的基础，其中不变量特征是一 个重要的理论。SIFt是最有效的尺度、旋转、亮度不变量局部特征之一，但算法复杂、计算时间长。分析 了SIFt的计算时间分配，通过计算关键点的邻域梯度直方图时动态修改采样步长，大大提高了SWr的 计算速度。分析了基于SIFt特征的图像匹配算法，提出了双向匹配算法，提高了图像匹配的准确率。实 验结果表明所提出的方法是有效的-Scale invariant feature transform(SI
Contourlet-pcnn
- 图像融合论文,基于非采样Contourlet变换与简化PCNN的图像融合-Image fusion papers, image fusion based on non-sampling Contourlet transform and simplify the PCNN
OV7670
- 图像传感器，体积小，工作电压低，提供单片VGA摄像头和影像处理器的所有功能。通过SCCB总线控制，可以输入整帧、子采样、取窗口等方式的各种分辨率8位影像数据。-The image sensor, small size, low operating voltage, with all the functionality of monolithic VGA camera and image processor. Controlled by SCCB bus, can enter various re
Combined-Compressive-Sampling-and-Image
- compressive sensing using OMP
ASM-2.2.1
- 对模型特征点周围的纹理信息进行采样，对比图像和模型训练集的纹理，找到纹理最接近的点即认为是特征点。作者这里比较纹理的工具是马氏距离。为了提高搜索的效率，作者还提到了多分辨率搜索周围像素纹理，对于粗糙的尺度，搜索范围大，对于细致的尺度，进行细致的搜索，提高了匹配的效率。-The texture information model feature points around the sampling, texture contrast image and model train sets, find
opencv-doc
- 图像数据操作（内存分配与释放，图像复制、设定和转换） 图像/视频的输入输出（支持文件或摄像头的输入，图像/视频文件的输出） 矩阵/向量数据操作及线性代数运算（矩阵乘积、矩阵方程求解、特征值、奇异值分解） 支持多种动态数据结构（链表、队列、数据集、树、图） 基本图像处理（去噪、边缘检测、角点检测、采样与插值、色彩变换、形态学处理、直方图、图像金字塔结构） 结构分析（连通域/分支、轮廓处理、距离转换、图像矩、模板匹配、霍夫变换、多项式逼近、曲线拟合、椭圆拟合、狄劳尼三角化）
Simple-sublinear-Fourier-sampling-master
- e: Compressed Sensing (Compressive Sensing (CS), known as Compressed Sensing, Compressed Sampling). The theory states: compressible signal can be much lower than the Nyquist criterion for sampling data, and still be able to accurately recover the ori
1126code
- 网站商城的后台框架和模板，在后台开发总会用的到- LBP returns the local binary pattern image or LBP histogram of an image. J LBP(I,R,N,MAPPING,MODE) returns either a local binary pattern coded image or the local binary pattern histogram of an intensity image
crmiv
- 从先验概率中采样，计算权重，中介真值程度度量，基于中介真值程度度量的图像分割包含优化类的几个简单示例程序。- Sampling a priori probability, calculate the weight, The true extent of the value of the intermediary measure, measure the true extent of the agency based on the value of image segmentation Opti