中文说明：
用基于稀疏表示和KSVD字典学习去噪方法在对数域对SAR图像抑斑，本方法相对于一些经典的SAR图像抑斑方法，抑斑效果大大提高。
English Description：
Compared with some classical SAR image speckle suppression methods, the speckle suppression effect of this method is greatly improved.
SAR image speckle suppression in logarithmic domain based on sparse representation and ksvd dictiona
关注次数： 449
下载次数： 1
文件大小： 11793KB
中文说明：
用基于稀疏表示和KSVD字典学习去噪方法在对数域对SAR图像抑斑，本方法相对于一些经典的SAR图像抑斑方法，抑斑效果大大提高。
English Description：
Compared with some classical SAR image speckle suppression methods, the speckle suppression effect of this method is greatly improved.
KSVD for SAR_LOG
................\baboon.raw
................\barb.raw
................\barbara.raw
................\barton.raw
................\canaletto.raw
................\coifman.raw
................\daubechies.raw
................\demo.m
................\demo2.asv
................\denoiseImageDCT.asv
................\denoiseImageDCT.m
................\denoiseImageGlobal.m
................\denoiseImageKSVD.asv
................\denoiseImageKSVD.m
................\displayDictionaryElementsAsImage.asv
................\displayDictionaryElementsAsImage.m
................\esi.m
................\finger.raw
................\fingerprint.png
................\fingerprint.raw
................\flinstones.png
................\func_ReadRaw.m
................\gererateSyntheticDictionaryAndData.m
................\globalTrainedDictionary.mat
................\goldhill.raw
................\house.png
................\KSVD.asv
................\KSVD.m
................\KSVD_NN.m
................\lena.png
................\lena.raw
................\lena1.png
................\lena_15a.bmp
................\lenna.raw
................\lincoln.raw
................\MOD.m
................\mriscan.raw
................\MSSIM.m
................\my_im2col.m
................\NN_BP.m
................\OMP.m
................\OMPerr.m
................\peppers256.png
................\pointEnhance.m
................\R.m
................\README.txt
................\sar1.bmp
................\sar2.bmp
................\sar3.bmp
................\sar31.bmp
................\sar32.bmp
................\sar4.bmp
................\sar6.bmp
................\sar61.bmp
................\sar62.bmp
................\small.jpg
................\SSIM.m
................\washington.bmp
................\xsarmodel1.bmp