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matlab_12codes_original
- 压缩包里包括:离散傅里叶变换、Zernike多项式各项的图形表示、洛伦兹曲线、TM模数值模拟、牛顿后向插值法、特征值求解、求解速率方程、小波函数增加水印、Q开关分析等等。-Compressed bundle includes: the discrete Fourier transform, Zernike polynomials each graphical representation of the Lorenz curve, the TM mode numerical simulation,
MATLAB
- MATLAB小波在语音信号压缩中的应用(含目录)-The MATLAB Wavelet voice signal compression application (including catalog)
MATLAB-SPIHT_v1.0_02-12-08
- MATLAB 实现基于小波变换的图像压缩编码算法SPIHT-Implement the wavelet-trees-based image coding algorithm SPIHT using MATLAB
WCS_OMP
- 基于离散小波变换和压缩感知理论的灰度图像压缩算法。-Grayscale image compression algorithm based on dwt and compressed sensing.
compression_dwt53
- 基于整数5/3小波的灰度图像自适应压缩和解压缩算法。-Grayscale image adaptive integer 5/3 wavelet-based compression and decompression algorithms.
MyIC_SVD
- 基于SVD和信息熵理论的小波域灰度图像无损压缩算法。-Wavelet domain based on SVD and information entropy theory grayscale images lossless compression algorithm.
wavelet
- wavelet小波变换的一维和二维操作,包括一维信号压缩以及二维图像压缩,以及结果分析-wavelet manipulation including 1D and 2D, and signal compression, as well as analysis of results
lift-wavelet
- 对信号进行一维提升小波分解,然后获取信号压缩阈值,进行信号压缩-For one-dimensional signal wavelet decomposition of ascension, and then obtain signal compression threshold, signal compression
CSomp
- 图像压缩感知 正交匹配追踪 小波变换-The image compression perception orthogonal matches track wavelet transform
waveletP-imagePcompression
- 基于小波的图像压缩 代码可以直接用 对于初学者非常有用-Wavelet-based image compression code can be used directly useful for beginners
wavelet_introduction
- 小波的特点和发展,波分析在一维信号处理中的应用,小波分析在图象分析中的应用,包括图象特征抽取,图像压缩,数据隐藏和图象水印-Wavelet characteristics and development, wave analysis of one-dimensional signal processing, wavelet analysis in image analysis, including image feature extraction, image compression, data
Wavelet_IRLS
- 压缩感知CS——采用小波变换进行稀疏表示,高斯随机矩阵为观测矩阵,重构算法为ILRS算法,对256*256的lena图处理,比较原图和IRLS算法在不同采样比例(0.74、0.5、0.3)下的重构效果,并各运行50次,比较算法性能PSNR和每次的运行时间-Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix
Wavelet_OMP
- 压缩感知CS——采用小波变换进行稀疏表示,高斯随机矩阵为观测矩阵,重构算法为OMP算法,对256*256的lena图处理,比较原图和OMP算法在不同采样比例(0.74、0.5、0.3)下的重构效果,并各运行50次,比较算法性能PSNR和每次的运行时间 -Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix
Wavelet_SP
- 压缩感知CS——采用小波变换进行稀疏表示,高斯随机矩阵为观测矩阵,重构算法为SP算法,对256*256的lena图处理,比较原图和SP算法在不同采样比例(0.74、0.5、0.3)下的重构效果,并各运行50次,比较算法性能PSNR和每次的运行时间-Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix and
Wavelet_ROMP
- 压缩感知CS——采用小波变换进行稀疏表示,高斯随机矩阵为观测矩阵,重构算法为ROMP算法,对256*256的lena图处理,比较原图和ROMP算法在不同采样比例(0.74、0.5、0.3)下的重构效果,并各运行50次,比较算法性能PSNR和每次的运行时间 -Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matr
Waveletddd
- 小波图像分析程序,从分解,压缩,到重构,非常详细-Wavelet image analysis program from decomposition, compression, to the reconstruction of very detailed
Tutorial1
- 基于小波的图像压缩程序,给出了对比图,并对压缩效果进行了统计-Statistical effect based on wavelet image compression program gives a comparison chart, and compression
Image-Compression
- 使用小波分解函数实现图像压缩 选择合适的图像进行处理 -Image compression choose the image processing using wavelet decomposition function
mutual-information
- 红外和可见光的匹配跟踪在军事、遥感等领域有着广泛的应用。针对灰度和图像特征存在比较大差异的红外和可见光图像,本文采用了最大互信息算法,结合形态学梯度和小波分解。互信息算法优点在于不需要对多模图像灰度间的关系做任何假设,不足之处在于它对图像空间信息的忽略而且计算时间较长。本文互信息结合多结构元的形态学梯度检测的图像边缘,可以使得图像匹配精度提高,还能改善局部极值的问题,再利用小波分解对图像进行压缩降低分辨率,可以减少互信息计算量。最后的实验数据表明在配准过程中互信息的计算速度得到了优化,匹配精度得
wavelet_JPEG2000
- jpeg2000图像压缩源代码,使用小波变换-the jpeg2000 image compression source code, using wavelet transform