RESUMO
Accurate quality assessment of fused images, such as combined visible and infrared radiation images, has become increasingly important with the rise in the use of image fusion systems. We bring together three approaches, applying two objective tasks (local target analysis and global target location) to two scenarios, together with subjective quality ratings and three computational metrics. Contrast pyramid, shift-invariant discrete wavelet transform, and dual-tree complex wavelet transform fusion are applied, as well as levels of JPEG2000 compression. The differing tasks are shown to be more or less appropriate for differentiating among fusion methods, and future directions pertaining to the creation of task-specific metrics are explored.
RESUMO
The increased interest in image fusion (combining images of two or more modalities such as infrared and visible light radiation) has led to a need for accurate and reliable image assessment methods. Previous work has often relied upon subjective quality ratings combined with some form of computational metric analysis. However, we have shown in previous work that such methods do not correlate well with how people perform in actual tasks utilising fused images. The current study presents the novel use of an eye-tracking paradigm to record how accurately participants could track an individual in various fused video displays. Participants were asked to track a man in camouflage outfit in various input videos (visible and infrared originals, a fused average of the inputs; and two different wavelet-based fused videos) whilst also carrying out a secondary button-press task. The results were analysed in two ways, once calculating accuracy across the whole video, and by dividing the video into three time sections based on video content. Although the pattern of results depends on the analysis, the accuracy for the inputs was generally found to be significantly worse than that for the fused displays. In conclusion, both approaches have good potential as new fused video assessment methods, depending on what task is carried out.