搜索资源列表
ndvi
- 生成归一化植被指数(NDVI)数据产品及图象产品的IDL源程序-Generate normalized difference vegetation index (NDVI) data products and image products, IDL source code
moravecxin
- 首先, 计算每个像素点的兴趣值, 即以该像素点为中心, 取一个w×w(如:5×5)的方形窗口, 计算0度、45度、90度、135度四个方向灰度差的平方和, 取其中的最小值作为该像素点的兴趣值。 其次，根据实际图像设定一个阈值，遍历图像以兴趣值大于该阈值的点为候选点。 最后，选一个一定大小的窗口，让该窗口遍历灰度图象，在此过程中取窗口中兴趣值最大的候选点为特征点，算法结束。 -First, calculate the value of each pixel of interest, t
Gray-entropy-one-threshold-
- 灰度熵与传统shannon熵的区别在于，灰度熵考虑了图像中目标和背景类内灰度级的均匀性，有较好的分割效果。-The difference of Gray entropy and shannon entropy is that the gray entropy considers the target and the background class grayscale image uniformity, and has better segmentated results.
dsp_bf533_videotest
- bf533 开发板，基于视频图像差分法变化检测 开发环境:visul dsp 5.0-the bf533 development board, based on the video image difference method change detection the development environment visul dsp 5.0
susan
- susan的理论知识 如图1所示，图片是白色背景，有一个颜色比较暗淡的矩形。在图片上有5个圆形区域。圆形区域表示的是掩码区域。把圆形区域内的每一个位置的像素值与圆心处的像素值相比较，那么圆中的的像素可以分为两类，一类是像素值与圆心处的像素值相近的，另一类是像素值与圆心的处的像素值相差比较大的。那么，把第一类（像素值与圆心处的像素值相近的）所组成的区域称为USAN，USAN的全称是“Univalue Segment Assimilating Nucleus”。图2 中显示了图1中的5个圆
d
- 关于帧差法的特征提取的代码，用于图像识别，和图像分割-On the frame difference method for feature extraction code for image recognition, image segmentation and
source
- 此代码主要是利用最邻近差值法，双线性插值法，高阶插值法实现图像的旋转以及缩放-This code is the difference between the use of the nearest neighbor method to achieve image rotation bilinear interpolation, higher-order interpolation and scaling
GLMCandLBPextraction
- 第一个程序提取了图像灰度级为64的灰度共生矩阵，并计算了能量，熵，对比度，相关性，逆差矩这5个参数.第二个程序可以提取彩色图像的LBP纹理特征，可以提取采样点为8、16、24的统一模式（u2）、旋转不变模式（ri）、统一旋转不变模式（riu2）的LBP值。-The first program to extract a grayscale image GLCM 64, and calculate the energy, entropy, contrast, correlation, inverse
bmptest
- 实现读取显示bmp图像,可以根据两幅图像的容差值进行图像处理，并具容差值可以设定，直观对比两幅图像的变化，保存显示处理结果-Achieve read bmp image display can be based on the difference between the two images, the image processing tolerance and a tolerance value can be set to change in visual comparison of the
The-Frame
- 本程序运用帧间差分法进行运动目标的检测，通过帧间差分法获得差分图像，然后运用数学形态学进行处理，突出运动目标-This procedure using the inter-frame difference method to detect moving targets, the difference image obtained by inter-frame difference, then processed using mathematical morphology, highlightin
bg
- This document contains implementation of background subtraction two images. which follows based on frame difference method.first frame taken as background and second frame taken as input image-This document contains implementation of background sub
ITopoLogicalOperator
- 运用ITopoLogicalOperator接口进行空间拓扑运算，例如几何图像的裁剪，分割，差值运算等-ITopoLogicalOperator interface using topological operations, such as geometric image cropping, split the difference operation, etc.
Retinex
- 基于Retinx 的图像增强算法，包括：图像增强、色差、白平衡等等。(Retinx based image enhancement algorithms, including: image enhancement, color difference, white balance and so on.)
7
- 7 基于纹理复杂度和差分的抗盲检测图像隐写算法(7 against blind detection based on texture complexity and difference image steganography algorithm)
图片
- OTSU算法也称最大类间差法，有时也称之为大津算法，被认为是图像分割中阈值选取的最佳算法，计算简单，不受图像亮度和对比度的影响，因此在数字图像处理上得到了广泛的应用。它是按图像的灰度特性,将图像分成背景和前景两部分.(Difference method OTSU algorithm called maximum class, sometimes called the Otsu algorithm, is considered to be the best algorithm, threshold
Hybrid SVD-WDR
- In this paper a new image compression technique is presented using Singular value decomposition (SVD) and wavelet difference reduction (WDR). In this we have done hybridization of these two techniques in order to achieve higher compression rate and b
灰度差分统计GLDS
- 得到原始图像的灰度差分图像，灰度差分直方图。(The gray difference image of the original image is obtained, and the gray difference histogram is obtained)
diff_coder
- 差值图片：从原图减去均值图片，编码及解码及测试代码(difference source coder: a difference image constructed by subtracting the pixel means from the original image)
JPEG lite
- 将图片分割成8*8的块然后进行DCT和量化，编码及解码(For further improvement each 8x8 block of the difference image can be transformed using a 2D DCT before quantizing and coding)
IJARCCE 200
- In this paper, the Detection of the Moving Object is done based on Background Subtraction & Frame Differencing techniques. A moving object can be detected by employing various methods such as, by taking the difference between two Images.