文件名称:ImgComBasedonWavletandNN
- 所属分类:
- 图形图像处理(光照,映射..)
- 资源属性:
- [Matlab] [源码]
- 上传时间:
- 2008-10-13
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- 19.49kb
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- 0次
- 提 供 者:
- 王**
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Matlab实现图像压缩与重构步骤
① 对图像进行小波分解,得到第一层分解的低频系数和高频系数。
② 保留低频系数,对高频系数进行基于神经网络的矢量量化编码,达到压缩。
③ 根据码书以w还原高频系数
④ 根据保留的低频系数和还原的高频系数重构图像
-Matlab realization image compression and the heavy
construction step (1) pair of picture carries on the wavelet to
decompose, obtains the first decomposition the low frequency
coefficient and the high frequency coefficient. (2) Retains the low
frequency coefficient, carries on to the high frequency coefficient
based on the nerve network vector quantification code, achieves the
compression. (3) To w returns to original state the low frequency
coefficient according to the code book and the return to original
state high frequency coefficient heavy composition which the high
frequency coefficient (4) basis retains likes
① 对图像进行小波分解,得到第一层分解的低频系数和高频系数。
② 保留低频系数,对高频系数进行基于神经网络的矢量量化编码,达到压缩。
③ 根据码书以w还原高频系数
④ 根据保留的低频系数和还原的高频系数重构图像
-Matlab realization image compression and the heavy
construction step (1) pair of picture carries on the wavelet to
decompose, obtains the first decomposition the low frequency
coefficient and the high frequency coefficient. (2) Retains the low
frequency coefficient, carries on to the high frequency coefficient
based on the nerve network vector quantification code, achieves the
compression. (3) To w returns to original state the low frequency
coefficient according to the code book and the return to original
state high frequency coefficient heavy composition which the high
frequency coefficient (4) basis retains likes
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压缩包 : 39709601imgcombasedonwavletandnn.rar 列表 matlab程序-基于小波变换与神经网络的图像压缩\wav_sofm.m matlab程序-基于小波变换与神经网络的图像压缩\小波变换&神经网络用于图像压缩.doc matlab程序-基于小波变换与神经网络的图像压缩