搜索资源列表
FISTA-master
- FISTA My implementation of an Fast Iterative Shrinkage Thresholding Algorithm on MATLAB. Based on the implementation discussed in: Beck, Amir, and Marc Teboulle. Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and
E1-空域增强
- 1-1、图象的灰度变换 对图象p1-03实施灰度平方根变换 1， 要求：显示变换前后2幅图象和2幅直方图，变换参数自行设定。 1-2、空域平滑 对图象p1-03施加高斯噪声和椒盐噪声并实施梯度倒数加权平滑法 要求：显示变换前后2幅图象，利用方差评价空域平滑的效果。 1-3、空间锐化 根据Sobel算子，按照公式4.3.8和公式4.3.9对图象p1-03实施空间锐化 要求：显示变换前后2幅图象。(1-1. Gray transformation of image The squa
锐化
- matlab图像锐化代码，包括sobel算子、拉普拉斯算子以及roberts梯度法三种锐化方式。(MATLAB image sharpening code, including the Sobel operator, Laplasse operator and the Roberts gradient method three sharpening methods.)
Hoglist
- 这是一个在图像处理或图像标注中用matlab提取图像梯度特征的一个程序(This is a program in image processing or image annotation using MATLAB to extract the features of the image gradient)
mfcGdiplusDemo
- 基于VS2010的GDI+程序，实现随机色清空背景、画笔使用、纯色画刷、图案画刷、线性渐变画刷、路径渐变画刷、纹理画刷、7种几何图形、文字-字体与布局输出、图像操作。(The VS2010 GDI+ program based on random color clear background, using solid color brush, brush, brush, brush, pattern of linear gradient path gradient brush, brush, 7
图像质量评价
- 融合图像质量评价，包括标准差，平均梯度，信息熵等(Fusion image quality evaluation, including standard deviation, average gradient, information entropy and so on)
L0smoothing
- Image Smoothing via L0 Gradient Minimization
functions
- 论文 Robust Image and Video Dehazing with Visual Artifact Suppression via Gradient Residual Minimization 的源码，有demo(the source code of paper "robust Image and Video Dehazing with Visual Artifact Suppression via Gradient Residual Minimization&quo
gauss-gamma窗函数
- 写成gauss-gamma双窗函数，计算含有相干斑噪声的sar图像的梯度(The gauss-gamma double window function is used to calculate the gradient of the SAR image with the speckle noise)
howto_net_gradient_alpha_double
- Imposing of one image on another using a transparent gradient.
edges-master
- 边缘检测算子 图像边缘信息主要集中在高频段，通常说图像锐化或检测边缘，实质就是高频滤波。我们知道微分运算是求信号的变化率，具有加强高频分量的作用。在空域运算中来说，对图像的锐化就是计算微分。由于数字图像的离散信号，微分运算就变成计算差分或梯度。图像处理中有多种边缘检测（梯度）算子，常用的包括普通一阶差分，Robert算子（交叉差分），Sobel算子等等，是基于寻找梯度强度。拉普拉斯算子（二阶差分）是基于过零点检测。通过计算梯度，设置阀值，得到边缘图像。(The image edge infor
GeoMatch_src
- 图像模板匹配，基于梯度向量点积，处理模板图像与搜索图像，寻找最佳匹配得分点(Image template matching based on gradient vector product)
代码
- 图像分割噪声分析，算法对椒盐噪声的抗干扰性分析，图像反转线性变换，.梯度算子检测边缘(Analysis of image segmentation noise\,Algorithm for anti-interference analysis of salt and pepper noise,,image inversion linear transformation, gradient operator edge detection.)
HOG 代码.docx
- HOG 方向梯度直方图（Histogram of Oriented Gradient, HOG）特征是一种在计算机视觉和图像处理中用来进行物体检测的特征描述子(The Histogram of Oriented Gradient (HOG) feature is a feature descr iptor used for object detection in computer vision and image processing.)
ddfapd
- 方向滤波和后验决策算法，利用图像的边缘特性，将梯度权重值加入，能够很好的改善插值后图像的伪影效果。(Directional filtering and posteriori decision algorithm, using the edge characteristics of the image, add the gradient weight value, which can improve the artifact effect of the interpolated image.)
hog-feature
- 方向梯度直方图（Histogram of Oriented Gradient, HOG）特征是一种在计算机视觉和图像处理中用来进行物体检测的特征描述子。它通过计算和统计图像局部区域的梯度方向直方图来构成特征。Hog特征结合SVM分类器已经被广泛应用于图像识别中，尤其在行人检测中获得了极大的成功。需要提醒的是，HOG+SVM进行行人检测的方法是法国研究人员Dalal在2005的CVPR上提出的，而如今虽然有很多行人检测算法不断提出，但基本都是以HOG+SVM的思路为主(The Histogram
morphology.tar
- Morphological transformations are some simple operations based on the image shape. It is normally performed on binary images. It needs two inputs, one is our original image, second one is called structuring element or kernel which decides the nature
soble
- 使用soble算子计算图片梯度，得到图片的梯度图片，可用于清晰度检测或边缘识别(Using Soble operator to calculate image gradient, get gradient picture of the picture, which can be used for clarity detection or edge recognition.)
05567108.pdf
- The sky region of restored images often appears serious noise and color distortion using classical dark channel prior algorithm. To address this is- sue, we propose an improved dark channel prior algorithm which recognizes the sky regions in hazy ima
八个方向的sobel边缘检测算法
- 利用八方向的sobel边缘检测，实现对图像多梯度的梯度检测，检测出的边缘信息更加平滑连续。(Eight direction Sobel edge detection is used to realize gradient detection of image multi gradient, and the edge information detected is more smooth and continuous.)