Computing visual target distinctness through selective filtering, statistical features, and visual patterns

This paper presents three computational visual distinctness measures, compu ted from image representational models based on selective filtering, statis tical features, and visual patterns, respectively. They are applied to quan tify the visual distinctness of targets in complex natural scenes. The meas ure that applies a simple decision rule to the distances between segregated visual patterns is shown (1) to predict human observer performance in sear ch and detection tasks on complex natural imagery, and (2) to correlate str ongly with visual target distinctness estimated by human observers. (C) 200 0 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(00)03101- 9].