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matlab课程设计:空间滤波增强
空域滤波就是在图像空间中借助模板对图像进行邻域操作。输出图像中每一个像素的取值都是通过模板对输入像素相应邻域内的像素值进行计算得到的。学会并掌握使用matlab进行图像的空域滤波,设计用户界面实现上述功能。。
1、采用matlab Guide设计图像界面,可以读入并显示图像,设计实现以下功能的按钮,点击相应的按钮在图像界面上可以显示相应的功能。
2 首先对一副图像人为增加噪声(使用imnoise函数);
3 对图像进行线性滤波;
4 对图像
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空间滤波图像复原,使用matlab实现,对位图文件进行加噪后,处理-Spatial filtering image restoration, the use of matlab implementation of bitmap file to add noise, the treatment
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Phase-based Opic Flow Algorithm, described in
Gautama, T. and Van Hulle, M.M. [2002]. A Phase-based Approach to the
Estimation of the Optical Flow Field Using Spatial Filtering.
IEEE Trans. Neural Networks, 13[5], 1127--1136.- Phase-based
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用matlab编写的程序集合,主要是完成括亮度变换、线性和非线性空间滤波、图像复原与配准、彩色图像处理、小波、图像数据压缩、形态学图像处理、识别-Matlab procedures used to prepare the collection, mainly including brightness achieve transformation, linear and nonlinear spatial filtering, image restoration and registration,
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一种基于相位的光流计算方法,该方法不同于以往基于微分的计算方法,而是采用空间滤波器,取得非常好的效果。该结果发表于IEEE Trans. Neural Networks,13(5), 1127--1136.
-Gautama, T. and Van Hulle, M.M. (2002). A Phase-based Approach to the Estimation
of the Optical Flow Field Using Spatial Filtering, IEEE Tr
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基于Gabor变换的图像纹理识别。
提出了一种改进的Gabor变换的图像纹理增强算法,将空域的纹理图像变换到联合空间频率域并将联合空间
频率域的能量分布作为掌纹的特征,Gobar滤波器在频域内对子块其主方向上频率能量分布进行滤波,特征向量进行了匹配
识别,增强特征纹线信息并对核心区域进行多方向空间频率能量滤波合成,同时也对滤波算法进行了优化,有效地减少了运
算量。-Gabor transform based image texture recognition. An improv
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实验数字图像的空间域滤波和频域滤的实验知道书,在matlab上实现。-Experimental digital image spatial filtering and frequency domain filtering of the experiment to know the book, in matlab to achieve.
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本书在介绍MATLAB编程基础知识之后,主要围绕数字图像处理的主干内容展开。这些内容包括:亮度变换、线性和非线性空间滤波、频率域滤波、图像复原与配准、彩色图像处理、小波、图像数据压缩、形态学图像处理、图像分割、区域和边界的表示与描述以及目标识别。-Book introduces the basics of MATLAB programming, the main focus on the backbone of the contents of digital image processing t
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matlab图像处理工具箱及空域滤波函数的使用。理解和掌握图像空域滤波原理和方法-matlab image processing toolbox and use of spatial filtering function. Understand and master the principles and methods of image spatial filter
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Opencv写的空间滤波包括最大最小中值滤波等等,借鉴数字图像处理matlab版page117 的函数,几何平均,算术平均,调和平均,反调和平局,中值,中点等-Opencv write spatial filtering, including maximum and minimum median filtering, etc., drawing on digital image processing matlab version page117 function, geometric mean,
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数字图像处理中matlab环境先的几个实用的滤波函数-With the aid of examples such as histogram equalization analysis and spatial filtering, this article explains the application of matlab in image processing.
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这是一个小型数字图像处理系统。提供打开、保存、图形变换、空间滤波和直方图处理等功能。-This is a small digital image processing system. Provide open, save, graphics transformation, spatial filtering and histogram processing functions.
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本文主要探讨了中值滤波以及高斯滤波两个空间低通滤波器,结合unsharp masking,、Canny 算子、Sobel算子、以及Laplace算子研究了高通滤波器的特性,掌握了边缘检测技术的原理,并对这一系列技术进行了对比。
doc文档最后附有USM、Sobel等算子实现的matlab源代码-This paper discusses the median filtering and Gaussian filtering both spatial low-pass filter, combi
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实验2绿叶变色,实验3图像数字化显示,实验4图像类型转换,实验5对比度增强,实验6直方图均衡化和规定化,实验7噪声添加和空域滤波,实验8边缘增强和边缘检测,实验9彩色图像增强,fft,dct,dwt变化及压缩,滤波器,实验20运动退化和维纳波复原,实验21图像的几何畸形校正等实验的代码和报告-Experiment 2 leaves change color, 3 digital image display, the image type conversion, 4 5 contrast enha
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能够实现图像的亮度变换、对数变换、亮度拉伸,直方图均衡化和空间滤波。-To achieve the brightness of the image transform, logarithmic transformation, brightness stretch, histogram equalization and spatial filtering.
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图像处理算法在空间域和频域的简单滤波等方面的实现,实现了像霍夫变换和k均值算法的图像分割算法。(Image processing algorithm in the spatial domain and frequency domain of simple filtering and other aspects of the realization of the image segmentation algorithm such as Hough transform and k-means alg
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给定或者生成空间滤波模板,利用卷积原理对于图像用于进行空间滤波(The given spatial filter template is used for spatial filtering)
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matlab图像处理:油画效果的实现,基于非线性空间滤波。(Oil painting effect based on nonlinear spatial filtering.)
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理解图像空间滤波的实现步骤,掌握平滑、锐化两类空间滤波的区别,了解线性与非线性滤波差别(Understand the realization steps of image spatial filtering, grasp the difference between smoothing and sharpening two types of spatial filtering, and understand the difference between linear and non-linear
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对图像进行基础操作,包括亮度变换,空域滤波,频域滤波,形态学处理(The basic operation of the image, including brightness transformation, spatial filtering, frequency domain filtering, morphological processing)
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