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Steerable Wavelet based fusion model for high-resolution remotely sensed image enhancement

机译:基于可控小波的融合模型用于高分辨率遥感影像增强

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High resolution image shows more detail information in Panchromatic(PAN) band and more spectral information in multi-spectral(MS) band. This paper aims at developing a new Steerable Wavelet Transform-Intensity Hue Saturation(STWT-IHS) fusion model considering the texture detail information of different direction of PAN band. The IHS transform of the multi-spectral image firstly gives the Intensity, Hue and Saturation bands. Thereafter, the PAN band and Intensity band were decomposed into different scales including direct-based detail scales. Then, the fused Intensity band is obtained by reconstruction with high frequency components of PAN band and low frequency components of Intensity image and IHS inverse transform generates the final fused MS image. After presenting STWT principle, the fusion technique scheme is advanced based STWT and IHS theory. PAN band and MS band1,2,3 of QUICKBIRD are used to access the quality of the fusion model. After selecting appropriate decomposition level for the model, the fusion scheme gives fused image, which is compared with generally used fusion algorithms (IHS, Mallat and SWT). The objectives of image fusion include enhancing the visibility of the image and improving the spatial resolution and the spectral information of the original image. For assessing quality of an image after fusion, information entropy and standard deviation are applied to assess spatial details of the fused images and correlation coefficient, bias index and warping degree for measuring distortion between the original image and fused image in terms of spectral information. For all the tested fusion algorithms, better result is obtained when STWT-IHS is used.
机译:高分辨率图像在全色(PAN)波段中显示更多详细信息,而在多光谱(MS)波段中显示更多光谱信息。本文旨在考虑PAN波段不同方向的纹理细节信息,开发一种新的可控小波变换-强度色相饱和度(STWT-IHS)融合模型。多光谱图像的IHS变换首先给出强度,色相和饱和度带。此后,将PAN波段和Intensity波段分解为不同的比例,包括基于直接的细节比例。然后,通过使用PAN频段的高频分量和强度图像的低频分量进行重构,获得融合的强度带,然后IHS逆变换生成最终的融合MS图像。在提出STWT原理之后,基于STWT和IHS理论提出了融合技术方案。 QUICKBIRD的PAN波段和MS波段1,2,3用于访问融合模型的质量。在为模型选择适当的分解级别之后,融合方案会给出融合图像,并将其与常用的融合算法(IHS,Mallat和SWT)进行比较。图像融合的目的包括增强图像的可见性以及改善原始图像的空间分辨率和光谱信息。为了评估融合后的图像的质量,信息熵和标准偏差用于评估融合图像的空间细节以及相关系数,偏置指数和翘曲度,以根据光谱信息来测量原始图像和融合图像之间的失真。对于所有测试的融合算法,使用STWT-IHS可获得更好的结果。

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