搜索资源列表
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matlab 图像Gaussian Blur 的实现 USM-Filter 带有GUI窗口-matlab implementation of the image Gaussian Blur with a GUI window, USM-Filter
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这时高斯模糊的源码,对做图像盲复原的同学可以参考-Then Gaussian blur of the source, to make the image blind restoration of the students can refer to the
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matlab function for estimation gaussian and motion blur parapeters
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将图形加以高斯噪声或者椒盐噪声。为图像处理的一种可靠的加噪方法。BLUR Test problem: digital image deblurring-Gaussian noise or the graphics to be salt and pepper noise. As a reliable image processing method with noise. BLUR Test problem: digital image deblurring
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cuda5 and matlab code for Gaussian filtering and parallel image processing code, we hope to help
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数字图像处理matlab实现,包括如下程序:
1.直方图规定化为高斯双峰函数
2.窗口形状自适应(十字形或矩形)的中值滤波
3.彩色图像目标提取并与背景图像合成
4.插值外推法的彩色图像饱和度调整
5.多种插值方法实现的图像放大和缩小
6.频域变换及分析
7.几何校正
8.插值外推法的黑白图像对比度增强
9.运动模糊矫正-Digital image processing matlab realize, including the following proce
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这个是matlab里基于LR算法对模拟运动模糊并且加入高斯噪声进行复原的算法-This is carried out in the recovery matlab LR algorithm based simulation of motion blur and add Gaussian noise algorithm
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这个算法是matlab里基于最小平方对模拟运动模糊并加入高斯噪声复原算法-This algorithm is based on a least squares matlab in analog motion blur and add Gaussian noise restoration algorithm
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这个是matlab里基于维纳滤波算法对模拟运动模糊并加入高斯噪声的图像进行复原的程序
-This is where Wiener filtering algorithm matlab simulation of motion blur and add Gaussian noise image recovery program based on conduct
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This Gaussian lvbo program please downing this matlab blur ok yes -This Gaussian lvbo program please downing this matlab blur ok yes
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matlab程序:清晰图像变换为不同程度的高斯模糊图像程序-Matlab: clear image transformation for different levels of gaussian blur image process
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Gaussian blur, followed by laplacian.
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主要编写的图像预处理步骤的代码,包括灰度化,二值化,高斯模糊,图像增强(The main preparation of the image preprocessing steps of the code, including grayscale, binary, Gaussian blur, image enhancement.)
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主要包括DIP 3/e—Student Projects的说明文档以及实验05-04的详细代码,实验的要求为:
Instruction manual:
(a) Implement a blurring filter as in Eq. (5.6-11).
(b) Blur image 5.26(a) in the +45o direction using T = 1, as in Fig. 5.26(b).
(c) Add Gaussian noise of 0 mean and
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采用基于梯度的算法,通过matlab实现高动态范围成像。高动态范围图像,相比普通的图像,可以提供更多的动态范围和图像细节,根据不同的曝光时间的低动态范围图像,利用每个曝光时间相对应最佳细节的低动态范围图像来合成最终高动态范围图像,能够更好的反映人真实环境中的视觉效果。这里采用的高斯模糊展示了高动态范围图像中超出取值范围的数值也是有用的,即使它们在转换成低动态范围图像的时候通常都要被裁掉。在原始的高动态范围图像中,这些像素都有非常大的亮度值。当图像模糊的时候,周围的像素亮度被“拉高”并且在色度映射
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