Multispectral super-resolution of tropical cyclone imagery using sparsity-based approaches

ABSTRACT

An aperture synthesis system produces ringing at sharp edges and other transitions in the observed field. In this article, we have developed an efficient multispectral deconvolution method, based on the Split Bregman total variation minimization technique, and it was successful in reducing image ringing, blurring, and distortion, while sharpening the image and preserving the information content. We also present a multispectral multi-frame super-resolution method that is robust to image noise and noise in the point spread function (PSF) and leads to additional improvements in spatial resolution. The methodologies are based on current research in sparse optimization and compressed sensing, which lead to unprecedented efficiencies in solving image reconstruction problems.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. IY also acknowledges support from the National Science Foundation [Grant DMS 1217239].