Component Decomposition-Based Hyperspectral Resolution Enhancement for Mineral Mapping

Puhong Duan,Jibao Lai,Robert Jackisch,Xudong Kang,Jian Kang,Richard Gloaguen,Pedram Ghamisi

doi:10.3390/rs12182903

Abstract

Combining both spectral and spatial information with enhanced resolution provides not only elaborated qualitative information on surfacing mineralogy but also mineral interactions of abundance, mixture, and structure. This enhancement in the resolutions helps geomineralogic features such as small intrusions and mineralization become detectable. In this paper, we investigate the potential of the resolution enhancement of hyperspectral images (HSIs) with the guidance of RGB images for mineral mapping. In more detail, a novel resolution enhancement method is proposed based on component decomposition. Inspired by the principle of the intrinsic image decomposition (IID) model, the HSI is viewed as the combination of a reflectance component and an illumination component. Based on this idea, the proposed method is comprised of several steps. First, the RGB image is transformed into the luminance component, blue-difference and red-difference chroma components (YCbCr), and the luminance channel is considered as the illumination component of the HSI with an ideal high spatial resolution. Then, the reflectance component of the ideal HSI is estimated with the downsampled HSI image and the downsampled luminance channel. Finally, the HSI with high resolution can be reconstructed by utilizing the obtained illumination and the reflectance components. Experimental results verify that the fused results can successfully achieve mineral mapping, producing better results qualitatively and quantitatively over single sensor data.

Highlights

Hyperspectral scanners, as a newly appearing technique in the mining field, have been extensively utilized to explore minerals, since hyperspectral images (HSIs) are able to record rich spectral information varying from visible to infrared wavelength in hundreds of spectral channels [1,2,3,4,5,6,7,8,9]
We propose an effective approach to enhance the spatial resolution of HSIs with the guidance of RGB image for mapping minerals, since RGB images are obtained in practical applications and have a higher spatial resolution with respect to other modalities
We can observe that the spectral reflectance of our method is closer to the reflectance of the raw HSI among all compared methods, which illustrates that our method performs well in preserving the spectral information of land covers

Summary

Introduction

Hyperspectral scanners, as a newly appearing technique in the mining field, have been extensively utilized to explore minerals, since hyperspectral images (HSIs) are able to record rich spectral information varying from visible to infrared wavelength in hundreds of spectral channels [1,2,3,4,5,6,7,8,9]. The fusion of hyperspectral and RGB images is an effective scheme to yield a higher spatial and spectral resolution data, which is helpful for mapping all kinds of minerals

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Conclusion