文件名称:lifting_97
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实现9/7小波正反变换
注1: 采用标准正交方法,对行列采用不同矩阵(和matlab里不同)
注2: 为了保证正交,所有边界处理,全部采用循环处理
注3: 正交性验证,将单位阵带入函数,输出仍是单位阵(matlab不具有此性质)
注4: 此程序是矩阵实现,所以图像水平分量和垂直分量估计被交换位置
注5: 此程序实现的是类小波(wavelet-like)变换,是介于小波包变换与小波变换之间的变换
注6: 此程序每层变换相对原图像矩阵,产生的矩阵都是正交阵,这和小波包一致
注7: 但小波变换每层产生的矩阵,是相对每个待分解子块的正交矩阵,而不是原图像的正交矩阵
注8: 且小波变换产生的正交矩阵维数,随分解层数2分减少
注9: 提升系数可以在MATLAB7.0以上版本,用liftwave( 9.7 )获取,这里直接给出,考虑兼容性
注10:由于MATLAB数组下标从1开始,所以注意奇偶序列的变化
注11:d为对偶上升,即预测;p为原上升,即更新-Note 1: The standard orthogonal method, the ranks of the different matrices (and matlab where different)
Note 2: In order to ensure orthogonality, all boundary treatment, all with recycling
Note 3: Orthogonal validation, the identity matrix into the function, the output is still the unit matrix (matlab does not have this property)
Note 4: This program is a matrix to achieve, so the image horizontal and vertical components is estimated to be swapped
Note 5: This class implements the wavelet (wavelet-like) transformation, is between the wavelet packet transform and wavelet transform between
Note 6: This procedure transforms each image relative to the original matrix, the resulting matrix are orthogonal matrix, consistent with this and wavelet packet
Note 7: But each generation wavelet transform matrix, is to be broken down for each sub-block relative to the orthogonal matrix, rather than the original image of the orthogonal matrix
Note 8: Wavelet transf
注1: 采用标准正交方法,对行列采用不同矩阵(和matlab里不同)
注2: 为了保证正交,所有边界处理,全部采用循环处理
注3: 正交性验证,将单位阵带入函数,输出仍是单位阵(matlab不具有此性质)
注4: 此程序是矩阵实现,所以图像水平分量和垂直分量估计被交换位置
注5: 此程序实现的是类小波(wavelet-like)变换,是介于小波包变换与小波变换之间的变换
注6: 此程序每层变换相对原图像矩阵,产生的矩阵都是正交阵,这和小波包一致
注7: 但小波变换每层产生的矩阵,是相对每个待分解子块的正交矩阵,而不是原图像的正交矩阵
注8: 且小波变换产生的正交矩阵维数,随分解层数2分减少
注9: 提升系数可以在MATLAB7.0以上版本,用liftwave( 9.7 )获取,这里直接给出,考虑兼容性
注10:由于MATLAB数组下标从1开始,所以注意奇偶序列的变化
注11:d为对偶上升,即预测;p为原上升,即更新-Note 1: The standard orthogonal method, the ranks of the different matrices (and matlab where different)
Note 2: In order to ensure orthogonality, all boundary treatment, all with recycling
Note 3: Orthogonal validation, the identity matrix into the function, the output is still the unit matrix (matlab does not have this property)
Note 4: This program is a matrix to achieve, so the image horizontal and vertical components is estimated to be swapped
Note 5: This class implements the wavelet (wavelet-like) transformation, is between the wavelet packet transform and wavelet transform between
Note 6: This procedure transforms each image relative to the original matrix, the resulting matrix are orthogonal matrix, consistent with this and wavelet packet
Note 7: But each generation wavelet transform matrix, is to be broken down for each sub-block relative to the orthogonal matrix, rather than the original image of the orthogonal matrix
Note 8: Wavelet transf
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