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subbands
- 小波分析子程序模型和原理结构，子程序模型，-wavelet and waveletcompile
print
- This the source code for embedding watermarks in the detail subbands -This is the source code for embedding watermarks in the detail subbands
AutomaticSpectra
- This toolbox is Automatic spectral analysis for Irregular sampling/Missing data, analysis of spectral subbands, Vector Autoregressive modeling and Detection. It requires ARMASA toolbox. This toolbox can be downloaded fro
MoAT7.1
- This paper identifies a novel feature space to address the problem of human face recognition from still images. This based on the PCA space of the features extracted by a new multiresolution analysis tool called
1
- Cognitive radio frequency spectrum detection-The spectrum sensing of a wideband frequency range is studied by dividing it into multiple subbands. It is assumed that in each subband either a primary user (PU) is active
ASA
- 自动谱分析：可用于丢失/采样/子束光谱分析；矢量自动迭代，可用于建模，故障诊断；-The applications of this additional toolbox are: - Automatic spectral analysis for Irregular sampling/Missing data, analysis of spectral subbands, - Vector Autoregressive mod
SPIH
- Progressive coding, another feature of the JPEG 2000 standard, means that the bit stream can be coded in such a way as to contain less-detailed information at the beginning of the stream and more detailed information as
tr-01-2005
- This makes it ideal for Internet/network applications—especially with large images and low bandwidths—as the image can be seen instantly on the decoding side, even with low-speed networks or image databases. The lower su
embeddinggara.m
- Embedding dwt for watermarkin tecnique, using dwt domain in many subbands and with average gain set before without any variance.
decomp_reconst
- Decompose image into subbands, denoise, and recompose again. fh = decomp_reconst(fn,Nsc,Nor,block,noise,parent) Javier Portilla, Univ. de Granada, 5/02 Last revision: 11/04-Decompose image into subbands, de
decomp_reconst_full
- Decompose image into subbands, denoise, and recompose again. fh = decomp_reconst(im,Nsc,Nor,block,noise,parent,covariance,optim,sig) covariance: are we considering covariance or just variance? optim: for
decomp_reconst_W
- Decompose image into subbands, denoise using BLS-GSM method, and recompose again. fh = decomp_reconst(im,Nsc,filter,block,noise,parent,covariance,optim,sig) im: image Nsc: number of scales filter: type
decomp_reconst_WU
- Decompose image into subbands (undecimated wavelet), denoise, and recompose again. fh = decomp_reconst_wavelet(im,Nsc,daub_order,block,noise,parent,covariance,optim,sig) im : image Nsc: Number of scales d
wavelet
- decompose the input images into subbands
scramble
- These routines scramble an audio file by moving around short, overlapping windows within a local window. They can be used to create new versions of existing recordings that preserve the spectral content over longer time
lpc-distrotion
- This file computes the distortion of speech files regarding to lpc model in different subbands.
ADAPTIVE-IMAGE-FUSION-ALGORITHM
- 针对低可见光图像和红外图像的特点,提出一种基于DT-CWT的自适应图像融合算法.该算法具有好的平移不变性和方向选择性,更适合于人类视觉.先对源图像作双树复小波变换,充分考虑各尺度分解层的系数特征,对 低通子带引入免疫克隆选择,根据统计评价准则定义亲和度函数,自适应获得最优融合权值 对高通子带则根据人类视觉特性定义局部方向对比度,并作为融合准则,突出和增强了各源图像的对比度与细节信息.实验结果表明: 与基于小波的融合结果相比较,本
subbands
- 图像经过小波变换之后提取子带系数源代码在MATLAB中的实现-subbands in matlab
2
- his paper presents a reversible data hiding method based on wavelet spread spectrum and histogram modification. Using the spread spectrum scheme, we embed data in the coefficients of integer wavelet transform in hi