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Simultaneous Fusion and Denoising of Panchromatic and Multispectral Satellite Images

机译：全色和多光谱卫星图像的同时融合和去噪

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摘要

To identify objects in satellite images, multispectral (MS) images with high spectral resolution and low spatial resolution, and panchromatic (Pan) images with high spatial resolution and low spectral resolution need to be fused. Several fusion methods such as the intensity-hue-saturation (IHS), the discrete wavelet transform, the discrete wavelet frame transform (DWFT), and the principal component analysis have been proposed in recent years to obtain images with both high spectral and spatial resolutions. In this paper, a hybrid fusion method for satellite images comprising both the IHS transform and the DWFT is proposed. This method tries to achieve the highest possible spectral and spatial resolutions with as small distortion in the fused image as possible. A comparison study between the proposed hybrid method and the traditional methods is presented in this paper. Different MS and Pan images from Landsat-5, Spot, Landsat-7, and IKONOS satellites are used in this comparison. The effect of noise on the proposed hybrid fusion method as well as the traditional fusion methods is studied. Experimental results show the superiority of the proposed hybrid method to the traditional methods. The results show also that a wavelet denoising step is required when fusion is performed at low signal-to-noise ratios.
机译：为了识别卫星图像中的对象，需要融合具有高光谱分辨率和低空间分辨率的多光谱（MS）图像以及具有高空间分辨率和低光谱分辨率的全色（Pan）图像。近年来，人们提出了几种融合方法，例如强度-色相饱和度（IHS），离散小波变换，离散小波帧变换（DWFT）和主成分分析，以获得具有高光谱和空间分辨率的图像。本文提出了一种既包含IHS变换又包含DWFT的卫星图像混合融合方法。该方法试图以尽可能小的融合图像失真实现最高的光谱和空间分辨率。本文对提出的混合方法与传统方法进行了比较研究。在此比较中，使用了来自Landsat-5，Spot，Landsat-7和IKONOS卫星的不同MS和Pan图像。研究了噪声对提出的混合融合方法以及传统融合方法的影响。实验结果表明，该混合方法优于传统方法。结果还表明，当以低信噪比执行融合时，需要进行小波去噪步骤。

著录项

  • 来源
    《Sensing and imaging》 |2012年第4期|119-141|共23页
  • 作者

    Amr M. Ragheb; Heba Osman; Alaa M. Abbas; Saleh M. Elkaffas; Tarek A. El-Tobely; S. Khamis; Mohamed E. Elhalawany; Mohamed E. Nasr; Moawad I. Dessouky; Waleed Al-Nuaimy; Fathi E. Abd El-Samie;

  • 作者单位

    Department of Electronics and Electrical Communications Engineering, Faculty of Engineering,Tanta University, Tanta, Egypt;

    Department of Electronics and Electrical Communications, Faculty of Electronic Engineering,Menoufia University, Menouf 32952, Egypt;

    Department of Electronics and Electrical Communications, Faculty of Electronic Engineering,Menoufia University, Menouf 32952, Egypt;

    Department of Information Technology, Institute of Graduate Studies and Research,Alexandria University, Alexandria, Egypt;

    Department of Computer and Automatic Control, Tanta University, Tanta, Egypt;

    Department of Electronics and Electrical Communications Engineering, Faculty of Engineering,Tanta University, Tanta, Egypt;

    Department of Electronics and Electrical Communications, Faculty of Electronic Engineering,Menoufia University, Menouf 32952, Egypt;

    Department of Electronics and Electrical Communications Engineering, Faculty of Engineering,Tanta University, Tanta, Egypt;

    Department of Electronics and Electrical Communications, Faculty of Electronic Engineering,Menoufia University, Menouf 32952, Egypt;

    Department of Electrical Engineering and Electronics, The University of Liverpool, Liverpool L69 3GJ, UK;

    Department of Electronics and Electrical Communications, Faculty of Electronic Engineering,Menoufia University, Menouf 32952, Egypt;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Image fusion; DWT, IHS transform; DWFT; Wavelet denoising;

    机译：图像融合;DWT;IHS转换;DWFT;小波去噪;

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