离散多小波变换 DMWT
This paper focuses on the multiwavelet transform and M -channel wavelet transform and their application in image processing via lifting scheme.
本论文主要围绕提升格式下的多小波变换和M通道小波变换及其在图像处理中的应用来进行研究。
参考来源 - 提升格式下的小波变换在图像处理中的算法研究The digital watermarking algorithm combined SVD and multi-wavelet transform.
结合SVD和多小波变换的数字水印算法。
参考来源 - 基于变换域的数字水印算法的研究Thirdly, SAR image compression based on multiwavelet transform is proposed.
然后,论文研究了基于多小波变换的SAR图像压缩。
参考来源 - 基于小波理论的SAR图像压缩算法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
多小波变换兼有对称性、正交性、光滑性和有限支撑等信号处理中的十分重要的性质，特别适用于图像的压缩编码。
Multiwavelet possesses such very important properties in signal processing as orthogonality, symmetry, smoothness, and short support, which is specially applicable to image coding for compression.
提出了一种用于多尺度边缘检测的小波变换滤波器系数的计算方法，并且以具体例子进行了检验，表明了该方法的有效性。
A method of calculating wavelet transformation filter coefficients for multiscale edge detection is given in this paper, and the efficiency of the method is clarified.
本文提出了一种基于离散二进小波变换的多尺度边缘检测和图像融合的方法，实现了特征级图像融合。
Regarding this, a novel feature level approach to image fusion is proposed based on discrete dyadic wavelet transform for multi-scale image edge detection.
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