Restoration and Reconstruction of AVHRR Images

Stephen E. Reichenbach, Daniel E. Koehler, Dennis W. Strelow

Research output: Contribution to journalArticle

24 Scopus citations

Abstract

This paper describes the design of small convolution kernels for the restoration and reconstruction of Advanced Very High Resolution Radiometer (AVHRR) images. The kernels are small enough to be implemented efficiently by convolution, yet effectively correct degradations and increase apparent resolution. The kernel derivation is based on a comprehensive, end-to-end system model that accounts for scene statistics, image acquisition blur, sampling effects, sensor noise, and postfilter reconstruction. The design maximizes image fidelity subject to explicit constraints on the spatial support and resolution of the kernel. The kernels can be designed with finer resolution than the image to perform partial reconstruction for geometric correction and other remapping operations. Experiments demonstrate that small kernels yield fidelity comparable to optimal unconstrained filters with less computation.

Original languageEnglish (US)
Pages (from-to)997-1007
Number of pages11
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume33
Issue number4
DOIs
StatePublished - Jul 1995

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)

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