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A multivalued image wavelet representation based on multiscale fundamental forms

机译:基于多尺度基本形式的多值图像小波表示

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A new wavelet representation for multivalued images is presented. The idea for this representation is based on the first fundamental form that provides a local measure for the contrast of a multivalued image. In this paper, this concept is extended toward multiscale fundamental forms using the dyadic wavelet transform of Mallat (1992). The multiscale fundamental forms provide a local measure for the contrast of a multivalued image at different scales. The representation allows for a multiscale edge description of multivalued images. A variety of applications is presented, including multispectral image fusion, color image enhancement and multivalued image noise filtering. In an experimental section, the presented techniques are compared to single valued and/or single scale algorithms that were previously described in the literature. The techniques, based on the new representation are demonstrated to outperform the others.
机译:提出了一种新的多值图像小波表示。这种表示的思想基于第一种基本形式,该形式为多值图像的对比度提供了局部度量。在本文中,使用Mallat(1992)的二进小波变换将该概念扩展到多尺度基本形式。多尺度基本形式为不同尺度的多值图像的对比度提供了局部度量。该表示允许对多值图像进行多尺度边缘描述。提出了多种应用,包括多光谱图像融合,彩色图像增强和多值图像噪声滤波。在实验部分中,将提出的技术与文献中先前描述的单值和/或单尺度算法进行比较。事实证明,基于新表示形式的技术要优于其他技术。

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