Dynamic stimulus enhancement with Gabor-based filtered images

Alan R. Pinkus; Miriam J. Poteet; Allan J. Pantle

doi:10.1117/12.778002

17 April 2008 Dynamic stimulus enhancement with Gabor-based filtered images

Alan R. Pinkus, Miriam J. Poteet, Allan J. Pantle

Proceedings Volume 6968, Signal Processing, Sensor Fusion, and Target Recognition XVII; 69681R (2008) https://doi.org/10.1117/12.778002
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

In an empirical study, observers gave ratings of their ability to detect a military target in filtered images of natural scenes. The purpose of the study was twofold. First, the absolute value of the convolution images generated with oriented Gabor filters of different scales and orientations, and pairs of filters (corner filters), provided brightness images which were evaluated as saliency maps of potential target locations. The generation of the saliency maps with oriented Gabor filters was modeled after the second-order processing of texture in the visual system. Second, two methods of presentation of the saliency maps were compared. With the flicker presentation method, a saliency map was flickered on and off at a 2-Hz rate and superimposed upon the image of the original scene. The flicker presentation method was designed to take advantage of the known properties of the magnocellular pathway of the visual system. A second method (toggle presentation) used simply for comparison, required observers to switch back and forth between the saliency image and the image of the original scene. Primary results were that (1) saliency images produced with corner filters were rated higher than those produced with simple Gabor filters, and (2) ratings obtained with the flicker method were higher than those obtained with the toggle method, with the greatest advantage for filters tuned to lower spatial frequencies. The second result suggests that the flicker presentation method holds considerable promise as a new technique for combining information (dynamic image fusion) from two or more independently obtained (e.g., multi-spectral) or processed images.

Citation Download Citation

Alan R. Pinkus, Miriam J. Poteet, and Allan J. Pantle "Dynamic stimulus enhancement with Gabor-based filtered images", Proc. SPIE 6968, Signal Processing, Sensor Fusion, and Target Recognition XVII, 69681R (17 April 2008); https://doi.org/10.1117/12.778002

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KEYWORDS

Image filtering

Image processing

Image fusion

Target detection

Image enhancement

Spatial frequencies

Visualization

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