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VCPPsuanfa
- 本程序用VC++语言开发,包括拉普拉斯锐化(边缘检测),中值滤波,均值滤波等,并且给出了测试图片,运行正确-This program was developed with VC language, including the Laplacian sharpening (edge detection), the median filter, mean filter, and gives the test image, run correctly
shuzituxiangchuli
- 作业一 要求 用C语言或者VC,VB,Matlab或其他语言完成如下实验: 1)打开一个BMP文件 2)将其局部区域的灰度值进行改变 3)另存为一个新的BMP文件 要求显示出原BMP图像和新BMP图像。 作业二 要求 1. 编程实现图像傅立叶高通、低通滤波。 2. 尝试傅立叶压缩。 作业三 要求 编程实现图像DCT高通、低通滤波。并与傅里叶变换比较。 作业四 要求 找一幅曝光不足的灰度(或彩色)图像,按照直方图均衡化方法进行处
TEMPLATETRANS
- 它是遥感数据处理程序。可以实现图像增强,包括图像平滑、中值滤波、梯度锐化、拉普拉斯锐化、位彩色编码。-It is the procedure of dealing with the remote sensing data.We can make the image enhancement with it,including the image smooth,media filtering,sharping,Laplace sharping,false color coding.
Matlab-image-filiter
- 用中值滤波,多维滤波,使用中心为-4,-8的拉普拉斯滤波器,高斯低通滤波,拉普拉斯滤波器进行滤波处理-Center of median filtering, multi-dimensional filtering,-4,-8 Laplace filter, the Gaussian low-pass filter, Laplacian filter to filter the
LOG
- 本程序是基于vc的log算子,进行边缘检测。log算子是拉普拉斯算子和高斯低通滤波的结合,希望我的程序对大家的学习有所帮助。-This procedure is based on the vc log operator, edge detection. log operator is a combination of Laplacian and Gaussian low-pass filter, and want my program to help everyone to learn.
ITemplateTranm
- 图像的处理功能如:图像平滑,中值滤波波,梯度锐化,拉普拉斯锐化,伪彩色代码 -The image processing functions such as: image smoothing, median filtering wave gradient sharpening, Laplacian sharpening, pseudo-color code
denoiseaenhance
- 非MATLAB库函数实现空域去噪(包括“3x3均值滤波”、“5x5均值滤波”、“3x3中值滤波” 、“5x5中值滤波”)和空域加强(包括“拉普拉斯算子”、“Roberts算子”、“Prewitt算子”、“Sobel算子)的原创MATLAB代码。-Non-MATLAB library functions the airspace denoising (including the 3x3 mean filter, 5x5 mean filter, 3x3 median filter " ,
java-image-processing
- JAVA图像处理读取BMP图像、用RGB获取灰度信息、直方图均衡化、拉普拉斯2阶滤波、平滑锐化、增强滤波、局部阀值处理、全局阀值处理等-Java image processing to read the BMP image, obtained by RGB gray level information, histogram equalization, 2nd order Laplace filtering, smoothing, sharpening, enhanced filtering, p
project03_03
- 本实验要求编写一个空域滤波的函数,以实现拉普拉斯增强技术-In this study, prepared at the request of a spatial filter function to Laplace enhancement technology
image_edge_detection
- 本代码是基于VC6.0的图像增强代码,程序支持读入、显示各种类型的彩色、灰度图像,图像增强先做平滑滤波去除噪声,再采用拉普拉斯算子实现边缘检测,并附带图像灰度直方图的显示功能。-This code is based on image enhancement VC6.0 code, the program supports reading, showing all kinds of color, grayscale image, image enhancement do first smoothi
denoising
- 实现图像的滤波与锐化,利用拉普拉斯算子实现锐化-Image filtering and sharpening, Laplacian sharpening
Body
- 医学图像处理,包括拉普拉斯变换,锐化,sobel变换,均值平滑滤波,伽马校正等。-Medical image processing, including the Laplace transform, sharpen, sobel transformation mean smoothing filter, and gamma correction.
Algorithm
- 图像处理的颜色空间转换,经典拉普拉斯,高斯等滤波处理算法,以及简单的地形校正算法实现源码-Image processing, color space conversion, the classic Laplace, Gauss filtering algorithm for processing, and the simple terrain correction algorithm to achieve source
Digital-Image-Processing
- 1 打开一个BMP文件,将其局部区域的灰度值进行改变,另存为一个新的BMP文件,要求显示出原BMP图像和新BMP图像。 2.编程实现图像傅立叶高通、低通滤波。 3.打开一幅图像,添加椒盐、高斯噪声,然后使用邻域平均法、中值滤波法、K邻近平均法进行平滑 4.打开一幅图像,利用Roberts梯度法、Sobel算子和拉普拉斯算子进行锐化,并比较结果。 5.编写一个程序,对输入的图像进行哈夫曼编码,显示原图像的熵、编码后的平均码字长度、并能够根据编码重建出图像
BoneDIP
- 使用多种方法处理生物医学图形图像,包含拉普拉斯和梯度锐化处理,然后进行均值滤波还有幂率处理。-Processing of biomedical graphics using a variety of methods, including Laplace and gradient sharpening, and then the mean filter there is a power rate processing.
amplify_spatial_Gdown_temporal_ideal
- 对图像进行空间分解,高斯空间滤波,时域滤波,拉普拉斯变换-Image space decomposition, the gaussian spatial filtering, temporal filtering, Laplace transform
amplify_spatial_lpyr_temporal_butter
- 对图像进行空间分解,高斯空间滤波,时域滤波,拉普拉斯变换-Image space decomposition, the gaussian spatial filtering, temporal filtering, Laplace transform
amplify_spatial_lpyr_temporal_ideal
- 对图像进行空间分解,高斯空间滤波,时域滤波,拉普拉斯变换-Image space decomposition, the gaussian spatial filtering, temporal filtering, Laplace transform
amplify_spatial_lpyr_temporal_iir
- 对图像进行空间分解,高斯空间滤波,时域滤波,拉普拉斯变换-Image space decomposition, the gaussian spatial filtering, temporal filtering, Laplace transform
build_GDown_stack
- 对图像进行空间分解,高斯空间滤波,时域滤波,拉普拉斯变换-Image space decomposition, the gaussian spatial filtering, temporal filtering, Laplace transform