Automatic removal of poor-quality images from digital image sequences

Abstract

This paper introduces a spatio-temporal technique for selecting or filtering out lower quality digital image frames. The technique is demonstrated on Electro-Optical/Infrared image sequences which suggests it is a candidate for exploiting reconnaissance (recce) imagery or can be a part of a recce subsystem. For human vision exploitation, a few poor quality image frames out of hundreds in a digital image sequence may be only a minor irritation when the sequence runs at the typical 30 frames per se cond. Of course, if that human needs to examine each frame, a system that automatically removes or enhances lower quality image frames could be beneficial. For machine vision subsystems, a few poor quality image frames could cause lower probability of recognition.The filter technique introduced in this paper can improve input into machine vision algorithms. Another application for this technique is digital transmission to filter out unwanted images prior to transmission or to selectively enhance the poor quality frames. A major portion of current research into quality in digital image sequences focuses on transmission systems where an input high quality image sequence can be compared to the lower quality image sequence receivved at the output of the transmission system. However, this paper shows a technique for juding the quality of the input image frames prior to transmission, without a transmission system or without any knowledge of the higher quality image input. The impact of digital image artifacts on the spatio-temporal quality are shown. The quality variations in the individual frames of the input image sequence are charted to show which frames are of lower quality and thus need filtering.