K-SVD_and_W_KSVD_Sparse_Representation

所属分类:图形图像处理
开发工具:matlab
文件大小:475KB
下载次数:20
上传日期:2017-09-09 09:59:15
上 传 者smile北
说明:  通过字典学习更新的方法,对图像信号进行稀疏化分解
(Through the method of learning and updating the dictionary, the image signals are sparse decomposed)

文件列表:
K-SVD_and_W_KSVD_Sparse_Representation (0, 2017-08-28)
K-SVD_and_W_KSVD_Sparse_Representation\K-SVD_SR (0, 2017-08-28)
K-SVD_and_W_KSVD_Sparse_Representation\K-SVD_SR\imnormalize.m (383, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\K-SVD_SR\KSVD.m (8070, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\K-SVD_SR\KSVD_Dictionaries.m (2593, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\K-SVD_SR\OMP.m (1078, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\K-SVD_SR\OMPerr.m (1062, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\K-SVD_SR\Plane.bmp (263224, 2015-05-13)
K-SVD_and_W_KSVD_Sparse_Representation\K-SVD_SR\showdict.m (2293, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\W-KSVD_SR (0, 2017-09-09)
K-SVD_and_W_KSVD_Sparse_Representation\W-KSVD_SR\imnormalize.asv (669, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\W-KSVD_SR\imnormalize.m (383, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\W-KSVD_SR\KSVD_Dictionaries.asv (2618, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\W-KSVD_SR\OMP.m (1078, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\W-KSVD_SR\OMPerr.m (1062, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\W-KSVD_SR\Plane.bmp (263224, 2015-05-13)
K-SVD_and_W_KSVD_Sparse_Representation\W-KSVD_SR\showdict.m (2293, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\W-KSVD_SR\W_KSVD.m (9333, 2015-05-24)
K-SVD_and_W_KSVD_Sparse_Representation\W-KSVD_SR\W_KSVD_Dictionaries.asv (3224, 2017-09-09)
K-SVD_and_W_KSVD_Sparse_Representation\W-KSVD_SR\W_KSVD_Dictionaries.m (3308, 2017-09-09)

======================================================================== 本文件夹内文件主要有:1.matlab文件:KSVD.m、imnormalize.m、 KSVD_Dictionaries.m、OMP.m、OMPerr.m和showdict.m 2.测试图像文件:Plane.bmp ======================================================================== 说明:1.主要实现K-SVD算法训练字典用于图像稀疏表示。在matlab中直接运行KSVD_Dictionaries.m 可以得到演示结果。 2. 想要学习代码内容请查阅文件夹中其余代码。

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