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program3
二阶B样条小波边缘检测
处理后的图像为多尺度下的边缘检测图像
还需要进行边缘图像的匹配(Second-order B-spline wavelet edge detection image processing for multi-scale edge detection to the edge of the image also need to match image)
- 2009-05-11 17:40:16下载
- 积分：1
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利用峰值信噪比对去噪性能进行比较
分别利用均值滤波、自适应滤波和中值滤波对噪声图像g1和g2进行滤波，利用峰值信噪比对去噪性能进行比较。(Respectively, using the mean filter, adaptive filtering and median filtering images g1 and g2 noise filtering, denoising performance comparison using the peak signal-to-noise ratio.)
- 2012-09-12 07:35:10下载
- 积分：1
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LevelSet_ChunmingLi_v0
李纯明博士的无需初始化模型的源代码，作者亲自写的。还有测试图象，相信对大家肯定有好处。(Economics Dr. initialization model without the source code, written by the author himself. There test image, I think we will benefit.)
- 2021-01-13 10:18:48下载
- 积分：1
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Face_test_luminance
MATLAB实现的 人脸检测定位,M文件,较为准确的(MATLAB realize Face Detection positioning, M files, more accurate)
- 2008-02-27 20:21:52下载
- 积分：1
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SPIHT
spiht 图形程序压缩代码 代码可用 请仔细研读 并适当修改为适合自己的 (SPIHT graphics program to compress code code available, please carefully read and amended as appropriate for their own)
- 2012-07-06 14:06:10下载
- 积分：1
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NSCT_zhu20182
说明： 用于医学图像融合CT和MRI灰度图像，MRI和PET的彩色图像融合(For medical image fusion)
- 2020-10-13 10:59:32下载
- 积分：1
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图像处理
说明： 简单图像压缩处理，正交变化，图像压缩灰度变化(Simple Image Compression Processing, Orthogonal Change, Gray Level Change of Image Compression)
- 2019-04-14 20:53:48下载
- 积分：1
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nighttime-dehazing-master
说明： 采用通道差的引导滤波进行大气光估计和明暗通道混合的夜间去雾(The guiding filter of channel difference is used for atmospheric light estimation and night defogging with mixed light and dark channels)
- 2021-03-22 18:23:29下载
- 积分：1
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数字图像处理_第三版_英_答案
《数字图像处理（第三版）》课后习题答案，作者冈萨雷斯(Answers to Exercises after Class of Digital Image Processing (Third Edition),author Gonzalez)
- 2019-06-10 10:54:09下载
- 积分：1
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wavelet_denosiy
说明： Donoho提出的小波阀值去噪的基本思想是将信号通过小波变换（采用Mallat算法）后，信号产生的小波系数含有信号的重要信息，将信号经小波分解后小波系数较大，噪声的小波系数较小，并且噪声的小波系数要小于信号的小波系数，通过选取一个合适的阀值，大于阀值的小波系数被认为是有信号产生的，应予以保留，小于阀值的则认为是噪声产生的，置为零从而达到去噪的目的。尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点。(The basic idea of wavelet threshold de-noising proposed by Donoho is that the wavelet coefficients generated by the signal after passing through the wavelet transform (Mallat algorithm) contain the important information of the signal. After the wavelet decomposition, the wavelet coefficients of the signal are larger, the wavelet coefficients of the noise are smaller, and the wavelet coefficients of the noise are smaller than the wavelet coefficients of the signal. By selecting a suitable threshold, the wavelet coefficients of the noise are larger than the valve The wavelet coefficients of values are considered to be generated by signals, which should be preserved. The ones less than the threshold are considered to be generated by noise, which is set to zero to achieve the purpose of denoising.)
- 2019-12-18 17:23:27下载
- 积分：1
