Anisotropic Scale Invariance Quantification Method for 2D Mixing Fields and Its Applications
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摘要: 由不同尺度过程或作用叠加而形成的混合场在地学领域很常见,研究如何量化这些场的尺度不变性以及如何刻画其各项异性特征具有重要意义.介绍了近期研发的图像各向异性尺度不变性模拟和分解方法,并将其应用于遥感图像处理中.该方法是将各向异性尺度不变性模拟(SIG)和分形滤波(S-A)方法融合的,对于任意二维场,先用S-A模型判断其是否为混合场.如果是混合场,用S-A模型对其进行模式分解,然后再运用SIG模型量化分解后的各组分的各向异性尺度不变性,并描述其具体变换特征.基于一幅混合遥感影像的应用实例表明,该方法能够有效地量化二维混合场的各向异性尺度不变性.此外,混合场只有在正确分解成不同尺度的组分之后才能得到合理的利用.
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关键词:
- 混合场 /
- 各向异性尺度不变性 /
- 广义尺度不变性理论 /
- 各向异性尺度不变性量化模型 /
- 能谱密度-面积模型.
Abstract: Mixing fields caused by processes and effects with different scales are very common in geosciences researches. It is important to work out methods to quantify anisotropic scale invariance for these fields. This paper puts forward a newly developed anisotropic scale invariance quantification and mixing data decomposition method for images and applies it to remote sensing image processing, which is an integrated model of the SIG (scale invariant generator) model and S-A (spectrum-area) model. For any 2D fields, S-A model is used to identify if it is a mixing field. If it is, decompose it into different components also by S-A. Then use SIG model to quantify the decomposed components' anisotropic scale invariance and describe their transformation characteristics. An application of processing a mixing remote sensing image demonstrates that this method is able to quantify anisotropic scale invariance for 2D mixing fields and mixing fields must be decomposed properly before application. -
图 4 根据图 3中的2个拐点构建的3个滤波器
Fig. 4. The three filters constructed according to the breaks in the S-A plot
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