<title>Resolution enhancement of ASTER shortwave and thermal infrared bands based on spectral similarity</title>

Abstract

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) consists of three subsystems divided by the wavelength region: Visible and Near-Infrared (VNIR), Shortwave Infrared (SWIR), and Thermal Infrared (TIR) subsystems. The VNIR, SWIR and TIR subsystems have 3, 6, and 5 spectral bands with the spatial resolution of 15, 30, and 90m, respectively. The purpose of this study is to propose an algorithm for generating SWIR and TIR imagery with a 15m resolution based on spectral similarity. In the algorithm, SWIR images are first super-resolved using VNIR images, and TIR images are then super-resolved using VNIR and super-resolved SWIR images. The first step is as follows: 1) degrade the resolution of the VNIR images to 30m by pixel aggregation with the point spread function (PSF) of SWIR, 2) generate a homogeneous pixel map with a 30m resolution from the original VNIR images, 3) generate a multi-way tree for VNIR and SWIR spectra by stepwise clustering for the 30m-resolution VNIR and SWIR images, 4) generate super-resolved SWIR images by allocating the most likely SWIR spectrum to each 15m-resolution pixel based on spectral similarity in VNIR using the 30m-resolution VNIR and SWIR images, and the multi-way tree, and 5) modify the super-resolved SWIR images using the PSF as to be fully restorable to the original images. The second step is similar, except that super-resolved TIR images are derived from both the VNIR and the super-resolved SWIR images. In the latter part of the study, the algorithm is validated using ASTER data.