Fusion of Hyperspectral and Multispectral Image Data for Enhancement of Spectral and Spatial Resolution

Abstract

ABSTRACT:Hyperspectral image enhancement has been a concern for the remote sensing society for detailed end member detection. Hyperspectral remote sensor collects images in hundreds of narrow, continuous spectral channels, whereas multispectral remote sensor collects images in relatively broader wavelength bands. However, the spatial resolution of the hyperspectral sensor image is comparatively lower than that of the multispectral. As a result, spectral signatures from different end members originate within a pixel, known as mixed pixels. This paper presents an approach for obtaining an image which has the spatial resolution of the multispectral image and spectral resolution of the hyperspectral image, by fusion of hyperspectral and multispectral image. The proposed methodology also addresses the band remapping problem, which arises due to different regions of spectral coverage by multispectral and hyperspectral images. Therefore we apply algorithms to restore the spatial information of the hyperspectral image by fusing hyperspectral bands with only those bands which come under each multispectral band range. The proposed methodology is applied over Henry Island, of the Sunderban eco-geographic province. The data is collected by the Hyperion hyperspectral sensor and LISS IV multispectral sensor.

Data Fusion for Increasing Monitoring Capabilities of Sentinel Optical Data in Marine Environment

“…An estimation of A and E can be achieved through optimization techniques that use iterations. Though, based on the studies in [8], [19] endmembers can be extracted from the hyperspectral image and then spectrally downsampled to the resolution of the multispectral image. Then, the linear mixing model is applied on M and matrix A is estimated through least squares.…”

“…According to unmixing-based fusion methods, the high spatial resolution image is a spectrally degraded form of the high spectral resolution image and vice versa, the high spectral resolution image is a spatially degraded form of the high spatial resolution image. In [7] and [8], the unmixing process was implemented sequentially on the HS and MS images resulting in endmembers extracted from the HS image and abundance matrices from the MS image by using the spectrally transformed HS endmembers. The fusion result is the multiplication of the HS endmembers with the MS abundance matrices.…”

“…Unfortunately, the lack of spectral libraries for sea water sets severe constraints in their use. In this study, a methodology similar to [7] and [8] has been applied because it is straightforward, requires short processing time and renders the interpretation of the fused image easier. The novelty of this paper doesn't lie on the development of new data fusion algorithms, but rather a) on the attempt to use an unmixingbased fusion process on S2 and S3 images for producing higher resolution ocean map products (e.g.…”

Fusion of Airborne Hyperspectral and WorldView2 Multispectral Images for Detailed Urban Land Cover Classification A case Study of Kuala Lumpur, Malaysia

“…However, in this technique, the spatial enhancement is limited to several principal components of the HS image. The most initial research was based on pan sharpening, like PCA-based techniques (Licciardi et al, 2012), CN sharpening, Gram-Schmidt sharpening (Maurer, 2013), and unmixing-based fusion (Chakravortty and Subramaniam, 2014). MS and HS sensors work in different regions of the electromagnetic spectrum; thus, band mapping another major problem arises (Khandelwal and Rajan, 2011).…”