搜索资源列表
LGIF
- 这是“Active contours driven by local and global intensity fitting energy with application to brain MR image segmentation”（简称LGIF模型）的MATLAB源代码。LGIF模型是非常重要局部区域活动轮廓模型, 它结合了CV模型和LBF模型各自的优点。-This is the "Active contours driven by local and global inten
SimpleImgCompressApp
- 可以按照要求的比例大小实现图像的压缩和解压功能！还可以调节图像灰度等！-As requested, the ratio of the size of image compression and decompression functions! You can also adjust the image intensity and so on!
Thres_ent
- Segmentation function for matlab : this fucntion convert an intensity image to a binary image by using Entropy-based method.
thresh_tool
- This tool launches a GUI for thresholding an intensity input image. A line on the histogram indicates the current threshold level. A binary image is displayed in the top right based on the level, click and drag the line. The output image updates auto
ImageDenoisingBasedonWaveletTransform
- 基于小波变换的图像去噪的matlab程序 程序使用说明： 1、软件应用平台：Matlab6.5或更高； 2、打开方法： 将文件所在目录设为工作目录，然后打开wavlet.fig,在noise提示框下输入噪声强度，在0-0.1之间（不能为零）。 然后点process按钮，就会显示实验结果，包括原图像，加噪图像，去噪图像的对比以及当前的psnr值。 wavlet.m是程序文件。 程序内容写在在程序的注释里。 阈值的更改没有实现可视化，在源程序中可以改。-Image d
fuzzyIntensityTransformation
- matlab implementation of image intensity transformation with fuzzy logic
INTENSITY-TRANSFORMATION
- Image Processing Algorithms:- All basic intensity transformation algorithms are present here.
abs
- 最简单的匹配算法，通过计算图像的灰度差来实现图像的匹配功能-The easiest match to achieve the image matching algorithm to calculate the image intensity difference
Intensity-Ihomogeneities
- This files are related to implementation of the article entitled "a level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI".
Fast-Tracking
- “Fast Tracking via Dense Spatio-Temporal Context Learning,” In ECCV 2014的源代码，效果非常好。-In this paper, we present a simple yet fast and robust algorithm which exploits the spatio-temporal context for visual tracking. Our approach formulates the spatio-te
Image-Growing-and-segmentation
- Segmentation by growing a region seed point using intensity mean measure-Segmentation by growing a region seed point using intensity mean measure
Wavelet-Based-Image-Segmentation
- It contains the methods to extract out the darker or lighter objects of various intensities and shapes (including faint/ low intensity objects) noisy or inhomogeneous background-It contains the methods to extract out the darker or lighter objects of
Image-Fusion-using-Cross-Bilateral-Filtering-base
- The Cross Bilateral filter can enhance the PSNR of multi focus images that is in image fuison. Bilateral filtering is a local, nonlinear and non- iterative technique which combines a classical low-pass filter with an edge stopping function that atten
prewwit
- The Prewitt operator is used in image processing, particularly within edge detection algorithms. Technically, it is a discrete differentiation operator, computing an approximation of the gradient of the image intensity function. At each point in the
pdf_tail1
- SAR图像强度概率密度函数与理论最佳拟合的比较-Comparison between the SAR image intensity probability density function and the theory of the best fitting...
A-Level-Set-Method-for-Image-Segmentatio
- A Level Set Method for Image Segmentation in the Presence of Intensity Inhomogeneities With Application in MRI
imnoise_bi
- J = imnoise(I,'localvar',IMAGE_INTENSITY,VAR) adds zero-mean, Gaussian noise to an image, I, where the local variance of the noise is a function of the image intensity values in I. IMAGE_INTENSITY and VAR are vectors of the same size, and P
deimnoise2_bi
- adds zero-mean, Gaussian noise to an image, I, where the local variance of the noise is a function of the image intensity values in I. IMAGE_INTENSITY and VAR are vectors of the same size, and PLOT(IMAGE_INTENSITY,VAR) plots the functional
图像的分析
- 可显示图像中指定点的坐标值、像素值、图像强度曲线、图像像素强度曲线、等值线、均值、标准差、协方差系数、质心、边界等。(It can display coordinate values, pixel values, image intensity curves, pixel intensity curves, contour lines, mean value, standard deviation, covariance coefficient, centroid, boundary and s
ctivrougr
- A fast and effective image fusion method is proposed for creating a highly informative fused image through merging multiple images. The proposed method is based on a two-scale decomposition of an image into a base layer containing large scale var