4 accepted papers
This paper proposes an effective and efficient destriping method for remote-sensing data. Destriping of remote-sensing data is an essential task because stripe noise not only degrades the visual quality but also seriously affects subsequent processing. We formulate the destriping problem as a convex…
A hyperspectral (HS) image has high spectral resolution information but low spatial resolution information. To get an HS image of high spatial and spectral resolution (high-spatial HS image), fusion techniques are actively studied, which synthesize an HS image of low spatial and high spectral resolu…
Acquiring high-resolution hyperspectral (HS) images is a very challenging task. To this end, hyperspectral pansharpening techniques have been widely studied, which estimate an HS image of high spatial and spectral resolution (high HS image) from a pair of an HS image of high spectral resolution but…
We propose a new regularization technique, named Hybrid Spatio-Spectral Total Variation (HSSTV), for hyperspectral image (HSI) restoration. Popular regularization techniques for HSIs are total variation functions (TV), and there have been proposed a variety of TVs for HSI restoration. However, they…