隐马尔可夫预测代码(含有大量案例)
所属分类:数学计算
开发工具:matlab
文件大小:1367KB
下载次数:13
上传日期:2020-06-22 09:47:46
上 传 者:
LoganLin
说明: 该算法用于matlab,主要用于马尔可夫算法
(THIS IS For markov algorithms)
This is a self-contained package including the 2-D DWT and inverse DWT
routines. However, the Idwt2.m and Iidwt2.m codes are slow and inefficient.
We did not try to optimize the codes at all. If you need faster routines,
you should download and install the Rice Wavelet Toolbox, which is available
via Rice DSP web page http://www.dsp.rice.edu
INSTALLATION:
download whmt.tar
tar -xf whmt.tar decomposes the tar file into many matlab .m files.
Main routines:
hdenoise.m : denoise a 2-D image using HMT with training. You can
also provide a pre-specified HMT model (no training).
hmttrain.m : train HMT model for give 2-D wavelet transform.
All wavelet coefficients at each scale within each subband
are tied together to avoid overfitting of the model.
hmtdeno.m : given 2-D wavelet transform and an HMT model, compute
the posterior state probabilities. Then, use filter
noisy wavelet coefficients to remove noise.
hmtmodel.m : obtain an HMT model for real-world images without
training. This model produces good denoising performance
for many real-world images.
Routines used by main routines:
emhht.m : one step of EM algorithm for HH subband. Used by hmttrain.m
emlht.m : same as emhht.m for LH subband.
emhlt.m : same as emhht.m for HL subband.
posthh.m : compute posterior state probabilities for HH subband.
Used by hmtdeno.m
postlh.m : same as posthh.m for LH subband
posthl.m : same as posthh.m for HL subband
2-D DWT and inverse DWT routines:
Idwt2.m : 2-D DWT
Iidwt2.m : 2-D inverse DWT
daubcqf.m : computes Daubechies wavelet filters
makeh1.m, up.m : routines used by Idwt2.m and Iidwt2.m
Other routines:
gauss.m : gaussian density function
testcon.m : compute convergence errors to stop HMT training
vec2mat.m : used by hmtmodel.m
Examples:
ex256.m : denoising example of 256x256 Lena image
generate a noisy 256x256 Lena. Train HMT and denoise.
ex512.m : example using 512x512 Lena image.
generate a noisy 512x512 Lena. Train HMT and denoise.
example2.m : denoising example 2.
generate a noisy Lena image. Use the HMT model in
lenamodel.hmt (no training) to denoise it.
example3.m : denoising example 3.
generate a noisy Lena image. Use hmtmodel.m to obtain
an HMT model for general real-world images. Then, use
HMT denoising.
Other files:
lena256, lena512 : binary file containing original 256x256 and
512x512 Lena images.
used in ex256.m, ex512.m, example2.m, and example3.m
lenamodel.mat : HMT model (ES,PS,MU,SI matrices) for 512x512
Lena with \sigma=0.1
Used in example2.m
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