Description: 程序代码说明 P0401：用Prewitt算子检测图像的边缘 P0402：用不同σ值的LoG算子检测图像的边缘 P0403：用Canny算子检测图像的边缘 P0404：图像的阈值分割 P0405：用水线阈值法分割图像 P0406：对矩阵进行四叉树分解 P0407：将图像分为文字和非文字的两个类别 P0408：形态学梯度检测二值图像的边缘 P0409：形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象-code P0401 Note : Prewitt operator to detect the edges in the image P0402 : different values of Getting operator to detect the edges in the image P0403 : Canny operator to detect the edges in the image P0404 : image thresholding segmentation P0405 : water line threshold method image segmentation P0406 : matrix Quadtree P0407 : images into text and non-text of the two categories P0408 : morphological gradient detection Binary Image Edge P0409 : morphology example -- Images from the PCB to remove all current lines, retaining only chip targets Platform: |
Size: 46403 |
Author:tian |
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Description: 程序代码说明 P0401：用Prewitt算子检测图像的边缘 P0402：用不同σ值的LoG算子检测图像的边缘 P0403：用Canny算子检测图像的边缘 P0404：图像的阈值分割 P0405：用水线阈值法分割图像 P0406：对矩阵进行四叉树分解 P0407：将图像分为文字和非文字的两个类别 P0408：形态学梯度检测二值图像的边缘 P0409：形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象-code P0401 Note : Prewitt operator to detect the edges in the image P0402 : different values of Getting operator to detect the edges in the image P0403 : Canny operator to detect the edges in the image P0404 : image thresholding segmentation P0405 : water line threshold method image segmentation P0406 : matrix Quadtree P0407 : images into text and non-text of the two categories P0408 : morphological gradient detection Binary Image Edge P0409 : morphology example-- Images from the PCB to remove all current lines, retaining only chip targets Platform: |
Size: 46080 |
Author:tian |
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Description: 程序代码说明
P0401：用Prewitt算子检测图像的边缘
P0402：用不同σ值的LoG算子检测图像的边缘
P0403：用Canny算子检测图像的边缘
P0404：图像的阈值分割
P0405：用水线阈值法分割图像
P0406：对矩阵进行四叉树分解
P0407：将图像分为文字和非文字的两个类别
P0408：形态学梯度检测二值图像的边缘
P0409：形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象
- Procedure code explanation
P0401: Examines the picture with the Prewitt operator the edge
P0402: Examines the picture with the different sigma value LoG
operator the edge
P0403: Examines the picture with the Canny operator the edge
P0404: Picture threshold value division
P0405: Divides the picture with the water line threshold value
law
P0406: Carries on to the matrix four forks the tree
decomposition
P0407: Divides into the writing and the non- writing two
categories the picture
P0408: The morphology gradient examines two values pictures the
edge
P0409: The morphology example 鈻♀枴deletes all electricity
streamline from the PCB picture, only retains the chip object Platform: |
Size: 40960 |
Author:李明 |
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Description: MATLAB源码，P0401：用Prewitt算子检测图像的边缘 P0402：用不同σ值的LoG算子检测图像的边缘 P0403：用Canny算子检测图像的边缘 P0404：图像的阈值分割 P0405：用水线阈值法分割图像 P0406：对矩阵进行四叉树分解 P0407：将图像分为文字和非文字的两个类别 P0408：形态学梯度检测二值图像的边缘 P0409：形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象-MATLAB source code, P0401: detection using Prewitt operator Edge P0402: different σ value Log Operators image edge detection P0403: using Canny edge detection image edge P0404: Image Thresholding P0405: water line threshold Image segmentation method P0406: for the matrix quadtree decomposition P0407: the image is divided into text and non-text for these two types of P0408: morphological gradient detected binary image of the edge of P0409: morphological examples- delete images from the PCB All current lines, retaining only the target chip Platform: |
Size: 571392 |
Author:钟小丽 |
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Description: 程序代码说明
P0401：用Prewitt算子检测图像的边缘
P0402：用不同σ值的LoG算子检测图像的边缘
P0403：用Canny算子检测图像的边缘
P0404：图像的阈值分割
P0405：用水线阈值法分割图像
P0406：对矩阵进行四叉树分解
P0407：将图像分为文字和非文字的两个类别
P0408：形态学梯度检测二值图像的边缘
P0409：形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象-Procedure Code Description P0401: detection using Prewitt operator Edge P0402: different σ value Log Operators image edge detection P0403: using Canny edge detection image edge P0404: Image Thresholding P0405: water line threshold Image segmentation method P0406: for the matrix quadtree decomposition P0407: the image is divided into text and non-text for these two types of P0408: morphological gradient detected binary image of the edge of P0409: morphological examples- from the PCB to remove all images current lines, retaining only the target chip Platform: |
Size: 40960 |
Author:张甲杰 |
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Description: canny算子进行边缘检测的源代码。
（1）首先对图像进行高斯滤波，去除噪声的影响；
（2）对滤波后图像计算梯度的幅值和方向
（3）对梯度幅值进行模极大值抑制
（4）双阈值确定边缘-canny edge detection operator to the source code. (1) First of all Gaussian image filtering to remove noise (2) after filtering the image calculated gradient amplitude and direction of (3) of the gradient amplitude for modulus maxima suppression (4) dual-threshold determine the edge Platform: |
Size: 1024 |
Author:章格 |
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Description: matlab实现商标文字分割~第一部分计算列梯度差，计算每个像素的列方向一定范围内（n）最大值和最小值的差距,统计该差值超过某一设定域值T的像素的个数，并将该统计个数存在 GY 向量。，第二部分计算行梯度差，计算每个像素的行方向一定范围内（n）最大值和最小值的差距，统计该差值超过某一设定域值T的像素的个数，并存在 GX 向量-matlab text segmentation ~ realize trademarks calculations are shown in the first part of the gradient difference, calculated for each pixel column direction of a certain range (n) the difference between maximum and minimum values, statistics of the difference exceeds a certain threshold T set of pixels of a few, and the statistics of the number of vectors exist GY. , The second part of the calculation line gradient difference, calculated for each pixel within a certain range direction (n) the difference between maximum and minimum values, statistics of the difference exceeds a certain threshold T set the number of pixels, and the existence of GX Vector Platform: |
Size: 1024 |
Author:eels |
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Description: 该方法采用反对称双正交小波分解系数计算视频帧的方向梯度向量，再统计由梯度向量角和模值构成的联合空间二维直方图，然后计算连续帧直方图之间的距离，得到两帧之间的不连续值，最后采用自适应阈值分割，检测出镜头边界。-This method is the use of anti-symmetric biorthogonal wavelet decomposition coefficients video frame the direction of gradient vector, and then statistics from the gradient vector angle and modulus values constitute the joint space of two-dimensional histogram, and then calculating the histogram for the distance between frames, by the two frames between the consecutive values, the final adaptive threshold segmentation, shot boundary detected. Platform: |
Size: 144384 |
Author:韩瑞冬 |
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Description: 对于一些图像来说，常用的边缘检测算法有时候无法设立合适的阈值将它们的梯度较小的模糊边缘检测出来。为了解决这个问题，有两种解决方法：将图像方差标准化，拉大模糊边缘的梯度值，或通过设置sigmoid函数，将像素所在区域的信息传递到梯度值中去，对其进行调整，就能找到合适阈值，有效地将模糊边缘提取出来。本程序把这两种算法实现并与与传统算法进行了比较。-For some images, the commonly used edge detection algorithm sometimes can not be an appropriate threshold for the gradient of their smaller fuzzy edge detected. To solve this problem, there are two solutions: the image variance standardization, widening the fuzzy edge of the gradient value, or by setting the sigmoid function pixel region to disseminate the message to the gradient values to adjust, on the can find a suitable threshold, effectively extracted fuzzy edge. This procedure of these two algorithms with the traditional algorithm. Platform: |
Size: 1024 |
Author:李思齐 |
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Description: 图像的各向异性扩散，利用matlab实现Perona_Malik算法，梯度阈值K通过对图像求解2-范数的方法迭代获得-Anisotropic diffusion images, using matlab to achieve Perona_Malik algorithm, the gradient threshold images by solving the K 2- norm method will be obtained Platform: |
Size: 49152 |
Author: zhou |
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Description: 提出了一种结合USFFT Curvelet 变换的各向异性扩散图像去噪模型。它有机结合了Curvelet 变换和各向
异性扩散（P-M扩散）两者的优点。通过P-范数方法选择合适的梯度阈值K，P-M扩散过程通过处理经过Curvelet
变换得到的图像的不同尺度的Curvelet 系数矩阵，实现了建立在对图像多尺度分析的基础上的新P-M扩散模型。
实验表明，新模型的处理结果能有效避免传统P-M 扩散出现的阶梯效应，同时更好地保留图像的纹理和细节。
关键词：图像去噪算法；各向异性扩散；Curvelet 变换；P-M 扩散-Abstract: An image de-noising model by integrating anisotropic diffusion with USFFT Curvelet transform was proposed,
which combined the strongpoint of Curvelet transform with anisotropic diffusion (P-M diffusion). By choosing appropriate
gradient threshold K through p-norms and carrying out the P-M diffusion process depend on the different scale matrixes
of Curvelet coefficient of the image from Curvelet transform iterations, as a result, the improved model made it
possible to carry out the new P-M diffusion de-noising process based on multi-scale analysis of the image. The experiment
results have demonstrated that the model can avert the stair-casing effect in the traditional P-M diffusion effectively
and keep the textures and details of images better. Platform: |
Size: 768000 |
Author:wangkun |
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Description: 针对传统Chan-Vese(CV)模型对公路路面破损图像分割的局限性，将图像梯度信息引入CV 模型，利用路面破损区域纹理与背景的
不同，对图像进行分割。引入梯度阈值，将图像的灰度信息和纹理信息相结合，从而使分割方法更具灵活性-Distress image segmentation on the road surface limitations for traditional Chan-Vese (CV) model, the introduction of image gradient information CV model, the use of the road surface texture and background of the damaged area of the different image segmentation. To introduce gradient threshold, combining image intensity and texture information, so that the segmentation method more flexibility Platform: |
Size: 1601536 |
Author:jim |
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Description: SEU2012年系统实验（DSP组）考试题目。计算并显示彩色图像在三个基色空间的直方图；用Prewitt梯度算子检测彩色图像的边缘，梯度阈值T自选，以检测到最佳边缘为目标
-SEU2012 system experiments (the DSP groups) exams. Calculate and display a histogram of the color image in the three primary color space Prewitt gradient operator to detect the edge of the color image, the gradient threshold T managed to detect the best edge for the target Platform: |
Size: 273408 |
Author:katheqiu |
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Description: 梯度锐化，可以使图像里部分像素更加凸显，如果选择合适的门限值，就可以使图像更加清新。-Gradient sharpening, you can make a more prominent part of the pixel in the image, if you select the appropriate threshold, you can make the image more fresh. Platform: |
Size: 8192 |
Author:丢丢 |
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Description: 基于梯度门限的图像过区 取与分割的源代码-Image based on gradient threshold transition region extraction and segmentation
Platform: |
Size: 6217728 |
Author:邱昌峰 |
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Description: 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 image by gradient threshold combined with the absolute value of the difference of atmospheric light and dark channel. And then we es- timate the transmission in sky and non-sky regions separately. At last, we en- hance the brightness and contrast of results. Experimental results show that our restored images are more natural and smooth in sky regions. Platform: |
Size: 6621184 |
Author:YaqingChang |
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Search - gradient threshold