Description: 一段对图像进行卷积的程序。可自定义区域处理方法进行卷积操作。自定义卷积和。-a programme of processing convolution of image.You can process convolution by defining area processing method and defining convolution sum by yourself. Platform: |
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Author:熊飞 |
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Description: 一段对图像进行卷积的程序。可自定义区域处理方法进行卷积操作。自定义卷积和。-a programme of processing convolution of image.You can process convolution by defining area processing method and defining convolution sum by yourself. Platform: |
Size: 678912 |
Author:熊飞 |
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Description: 图像区域处理的c语言实现，包括高通、低通滤波，边缘检测等。-image processing region of c language, including high- and low-pass filtering, edge detection. Platform: |
Size: 72704 |
Author:唐秀全 |
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Description: Convolution of images allows for image alterations that enable the creation of new images from old ones. 此源码包含十分详尽的Bitmap位图卷积实现方法-Convolution of images allows for image alt erations that enable the creation of new images from old ones. This source includes very detailed Bitmap bitmap deconvolution method Platform: |
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Author: |
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Description: 实验内容：
1．求下列3个模板的频率响应，并显示其三维图形；选择一幅图
像，利用这3个模板分别对该图像进行卷积运算，将卷积运算
获得的图像与原始图像进行比较，说明各模板的类型以及模板
（b）、（c）的区别与联系。
2. 选择一幅图像，对其进行离散Fourier变换，仅利用其相位谱重构原图像，然后仅利用其振幅谱重构原图像，比较实验结果；
选择两幅不同类型的图像，分别进行Fourier变换，交换二者的相位谱后求Fourier反变换，比较实验结果，说明图像Fourier相位谱的重要性。-Experimental contents: 1. Template for the following three frequency response and to show its three-dimensional graphics select an image using the three templates, respectively, of the image convolution operation, the convolution operation to obtain the images were compared with the original image to illustrate the template the type of template (b), (c) the difference with the contact. 2. Select an image, its discrete Fourier transform, only to use its phase spectrum remodeling the original image, and then only the use of its amplitude spectrum reconstruction of the original image to compare experimental results choice of two different types of images, respectively Fourier Transform, the exchange between the two after the phase spectrum for Fourier Transform, compare experimental results to illustrate the image of the importance of Fourier phase spectrum. Platform: |
Size: 1024 |
Author:syq |
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Description: 本程序提供了邻近值插值和三次卷积插值两种插值方法，可实现图像的任意比例放大缩小和任意角度的旋转，但由于本人不会MFC编程，所以所有变换结果必须到相应文件夹下（必须同时存放图形文件和程序）查看。-This procedure provided a neighboring value of interpolation and cubic convolution interpolation of two interpolation methods, can realize an arbitrary ratio of image zoom and rotation of any angle, but because I will not MFC programming, so all results must be to transform the corresponding folder (must be stored graphics files and programs) to view. Platform: |
Size: 3072 |
Author:清枫 |
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Description: 本程序实现了Gabor滤波器的三维显示并对一幅图像通过频域卷积实现了1个尺度6个方向的Gabor滤波显示-This procedure achieved a Gabor filter and a three-dimensional display image through frequency-domain convolution achieved a scale 6 shows the direction of the Gabor filtering Platform: |
Size: 1024 |
Author:朱宇 |
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Description: 上课时做的matlab图像处理实验，包括卷积，拉普拉斯变换，罗伯特算子，种子算法，-Matlab class to do the image processing experiments, including convolution, Laplace transform, Robert operator, seed algorithm, and so on Platform: |
Size: 245760 |
Author:张彩 |
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Description: Canny进行边缘检测，得到图像的边缘，然后sobel算子对图像边缘进行卷积，然后用Hough变换进行直线提取。-Canny edge detection to obtain the edge image, and then sobel edge operator for convolution, and then use the Hough transform for straight line extraction. Platform: |
Size: 1024 |
Author:mayan |
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Description: The present report outlines the design, implementation and performance of the application of Hough
Transform (HT) to detect circles in arbitrary pictures.
Detecting circles in arbitrary pictures involves a two step process in this project. First, edges within the
image have to be detected then, by means of a voting mechanism the most probable circles will be
located.
Edge detection goal is to look for boundary locations that naturally happen between objects. Objects
normally have continuous intensity values therefore sudden changes in that pattern might indicate a
boundary condition. Changes of intensity in one direction can be calculated by the gradient operator
however, noise can alter meaningful edges. Convolution is then normally applied to account for a small
amount of smoothing, thus reducing noise.-The present report outlines the design, implementation and performance of the application of Hough
Transform (HT) to detect circles in arbitrary pictures.
Detecting circles in arbitrary pictures involves a two step process in this project. First, edges within the
image have to be detected then, by means of a voting mechanism the most probable circles will be
located.
Edge detection goal is to look for boundary locations that naturally happen between objects. Objects
normally have continuous intensity values therefore sudden changes in that pattern might indicate a
boundary condition. Changes of intensity in one direction can be calculated by the gradient operator
however, noise can alter meaningful edges. Convolution is then normally applied to account for a small
amount of smoothing, thus reducing noise. Platform: |
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Author:donna |
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Description: 数字图象处理教程
INTRODUCTION 4
DIGITAL IMAGE DEFINITIONS 5
COMMON VALUES 6
CHARACTERISTICS OF IMAGE OPERATIONS 7
TYPES OF OPERATIONS 7
TYPES OF NEIGHBORHOODS 8
VIDEO PARAMETERS 9
TOOLS 9
CONVOLUTION 10
PROPERTIES OF CONVOLUTION 10
FOURIER TRANSFORMS 10
PROPERTIES OF FOURIER TRANSFORMS 11
IMPORTANCE OF PHASE AND MAGNITUDE 14
CIRCULARLY SYMMETRIC SIGNALS 15
EXAMPLES OF 2D SIGNALS AND TRANSFORMS 15
STATISTICS 16
PROBABILITY DISTRIBUTION FUNCTION OF THE BRIGHTNESSES 16
PROBABILITY DENSITY FUNCTION OF THE BRIGHTNESSES 16
AVERAGE 18
STANDARD DEVIATION 19
COEFFICIENT-OF-VARIATION 19
PERCENTILES 19-INTRODUCTION 4
DIGITAL IMAGE DEFINITIONS 5
COMMON VALUES 6
CHARACTERISTICS OF IMAGE OPERATIONS 7
TYPES OF OPERATIONS 7
TYPES OF NEIGHBORHOODS 8
VIDEO PARAMETERS 9
TOOLS 9
CONVOLUTION 10
PROPERTIES OF CONVOLUTION 10
FOURIER TRANSFORMS 10
PROPERTIES OF FOURIER TRANSFORMS 11
IMPORTANCE OF PHASE AND MAGNITUDE 14
CIRCULARLY SYMMETRIC SIGNALS 15
EXAMPLES OF 2D SIGNALS AND TRANSFORMS 15
STATISTICS 16
PROBABILITY DISTRIBUTION FUNCTION OF THE BRIGHTNESSES 16
PROBABILITY DENSITY FUNCTION OF THE BRIGHTNESSES 16
AVERAGE 18
STANDARD DEVIATION 19
COEFFICIENT-OF-VARIATION 19
PERCENTILES 19
MODE 20
SIGNALTONOISE RATIO 20
CONTOUR REPRESENTATIONS 21
CHAIN CODE 21
CHAIN CODE PROPERTIES 22
CRACK CODE 22
RUN CODES 23
PERCEPTION 23
BRIGHTNESS SENSITIVITY 23
WAVELENGTH SENSITIVITY 24
STIMULUS SENSITIVITY 24
SPATIAL FREQUENCY SENSITIVITY 25
COLOR SENSITIVITY 26
STANDARD OBSERVER 26
CIE CHROMATICITY COORDINATES 26
OPTICAL ILLUSIONS 28
IMAGE SAMPLING 30
SAMPLING DENSITY FO Platform: |
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Author:sean |
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Description: convolution of the image with a bank of even-symmetric
linear filters followed by half-wave rectification to give a set of responses Platform: |
Size: 1024 |
Author:yashar |
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Description: （1） 先由原始图像（任选）产生待恢复的图像；(产生方法如下：冲激函数为 ，将原始图像与冲激函数卷积产生模糊，然后再迭加均值为0，方差为8，16，32的高斯随机噪声而得到一组待恢复的图像。分别用逆滤波和维纳滤波恢复模糊后的图像。-(1) The first be the original image (optional) produces the image to be restored (generated as follows: impulse function, the original image with the impulse function, convolution of the effect of blurring, and then superimposed mean 0, variance 8,16,32 Gaussian random noise and get a group of images to be restored. were used to inverse filter and Wiener filter after the resumption of blurred images. Platform: |
Size: 180224 |
Author:紫瓶 |
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Description: 使用gabor函数对图像进行卷积操作，对学习图像滤波很有帮助-Gabor function image using the convolution operation, very helpful for learning image filter Platform: |
Size: 1024 |
Author:李若彤 |
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Description: 含有多种卷积核达到图像模糊，低通、高通滤波，边缘检测等目的，并且可自定义卷积核。-Contains a variety of convolution to the image fuzzy, low pass, high pass filter, edge detection purposes, and can be customized convolution. Platform: |
Size: 674816 |
Author:云中帆 |
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Description: 对原始图像在水平方向和垂直方向与2个滤波器(低通、高通)相卷积，可以得到4块面积为原图像1/4的子图，分别为水平方向低频和垂直方向低频(HH)、水平方向低频和垂直方向高频(HG)、水平方向高频和垂直方向低频(GH)、水平方向高频和垂直方向高频(GG)。-The original image in the horizontal direction and vertical direction and two filters (low pass, high pass) with convolution, you can get the original image area of 4 1/4 graph, respectively, horizontal and vertical direction low frequency ( HH), horizontal and vertical high-frequency low-frequency (HG), horizontal and vertical high-frequency low-frequency (GH), horizontal and vertical high-frequency high-frequency (GG). Platform: |
Size: 1024 |
Author:yuanyuan |
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Description: Convolution filtering is a technique that can be used for a wide array of image processing
tasks, some of which may include smoothing and edge detection. In this document we show
how a separable convolution filter can be implemented in NVIDIA CUDA and provide
some guidelines for performance optimizations. Platform: |
Size: 3926016 |
Author:vgaliano |
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Description: Here is a function of image convolution method that may help you understand the principle Platform: |
Size: 2180 |
Author:Badroubourdour |
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Search - convolution of image