Psychometric Correlates of the Effects of Image-Enhancing Algorithms on Visual Performance
Abstract
Future military image acquiring devices will have computational capabilities that will allow agile, realtime image enhancement. In preparing for such devices, numerous image enhancement algorithms should be studied; however, these algorithms need evaluating in terms of human visual performance using military-relevant imagery. Evaluating these algorithms through objective performance measures requires extensive time and resources. We investigated subjective methods for down-selecting algorithms to be studied in future research, and thus, provide a methodology for down-selection, Imagery was processed using six algorithms and then ranked along with two baselines through the method of paired comparisons and the method of magnitude estimation, in terms of subjective attitude. These rankings were then compared to objective performance measures: reaction times and errors in finding targets in the processed imagery. In general, we found associations between subjective and objective measures. This leads us to believe that subjective assessment may provide an easy and fast way for down-selecting algorithms but at the same time should not be used in place of objective performance-based measures.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 01, 2006
- Accession Number
- ADA444633
Entities
People
- Alan Pinkus
- Eric L. Heft
- George Reis
- Kelly Neriani
Organizations
- Air Force Research Laboratory