RESTORATION AND RECONSTRUCTION OF AVHRR IMAGES

This paper describes the design of small convolution kernels for the r estoration and reconstruction of Advanced Very High Resolution Radiome ter (AVHRR) images, The kernels are small enough to be implemented eff iciently by convolution, yet effectively correct degradations and incr ease apparent resolution, The kernel derivation is based on a comprehe nsive, end-to-end system model that accounts for scene statistics, ima ge acquisition blur, sampling effects, sensor noise, and postfilter re construction. The design maximizes image fidelity subject to explicit constraints on the spatial support and resolution of the kernel; The k ernels can be designed with finer resolution than the image to perform partial reconstruction for geometric correction and other remapping o perations, Experiments demonstrate that small kernels yield fidelity c omparable to optimal unconstrained filters with less computation.