Fusion of Hyperspectral and Panchromatic Images using Spectral Uumixing Results

TL;DR

This paper presents a data fusion method combining spectral unmixing of hyperspectral images with segmentation of panchromatic images to enhance spatial and spectral information in remote sensing data.

Contribution

It introduces a novel fusion approach that leverages spectral unmixing and segmentation results to improve hyperspectral and panchromatic image integration.

Findings

Effective combination of hyperspectral and panchromatic data

Improved spatial and spectral information in fused images

Validated on AVRIS Indian Pines dataset

Abstract

Hyperspectral imaging, due to providing high spectral resolution images, is one of the most important tools in the remote sensing field. Because of technological restrictions hyperspectral sensors has a limited spatial resolution. On the other hand panchromatic image has a better spatial resolution. Combining this information together can provide a better understanding of the target scene. Spectral unmixing of mixed pixels in hyperspectral images results in spectral signature and abundance fractions of endmembers but gives no information about their location in a mixed pixel. In this paper we have used spectral unmixing results of hyperspectral images and segmentation results of panchromatic image for data fusion. The proposed method has been applied on simulated data using AVRIS Indian Pines datasets. Results show that this method can effectively combine information in hyperspectral and panchromatic images.