The prevalence of image fusion---the combination of images of different modalities, such as visible and infrared radiation---has increased the demand for accurate methods of image-quality assessment. The current study used a signal-detection paradigm, identifying the presence or absence of a target in briefly presented images followed by an energy mask, which was compared with computational metric and subjective quality assessment results. In Study 1, 18 participants were presented with fused infrared-visible light images, with a soldier either present or not. Two independent variables, image-fusion method (averaging, contrast pyramid, dual-tree complex wavelet transform) and JPEG compression (no compression, low and high compression), were used in a repeated-measures design. Participants were presented with images and asked to state whether or not they detected the target. In addition, subjective ratings and metric results were obtained. This process was repeated in Study 2, using JPEG2000 compression. The results showed a significant effect for fusion but not compression in JPEG2000 images, while JPEG images showed significant effects for both fusion and compression. Subjective ratings differed, especially for JPEG2000 images, while metric results for both JPEG and JPEG2000 showed similar trends. These results indicate that objective and subjective ratings can differ significantly, and subjective ratings should, therefore, be used with care.

-Image fusion is the process of combining images of differing modalities, such as visible and infrared (IR) images. Significant work has recently been carried out comparing methods of fused image assessment, with findings strongly suggesting that a task-centred approach would be beneficial to the assessment process. The current paper reports a pilot study analysing eye movements of participants involved in four tasks. The first and second tasks involved tracking a human figure wearing camouflage clothing walking through thick undergrowth at light and dark luminance levels, whilst the third and fourth task required tracking an individual in a crowd, again at two luminance levels. Participants were shown the original visible and IR images individually, pixelaveraged, contrast pyramid, and dual-tree complex wavelet fused video sequences. They viewed each display and sequence three times to compare intersubject scanpath variability. This paper describes the initial analysis of the eye-tracking data gathered from the pilot study. These were also compared with computational metric assessment of the image sequences.

-Image fusion isfinding increasing application in areas such as medical imaging, remote sensing or military surveillance using sensor networks. Many ofthese applications demand highly compressed data combined with error resilient coding due to the characteristics of the communication channeL In this respect, JPEG2000 has many advantages over previous image coding standards.This paper evaluates and compares quality metricsfor lossy compression using JPEG2000. Three representative image fusion algorithms: simple averaging, contrast pyramid and dual-tree complex wavelet transform basedfusion have been considered. Numerous infrared and visible test images have been used. We compare these results with a psychophysical study where participants were asked to perform specific tasks and assess imagefusion quality.The results show that there is a correlation between most of the metrics and the psychophysical evaluation. They also indicate that selection of the correct fusion method has more impact on performance than the presence ofcompression.

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.

Abstract— The problem of assessing the quality of fused images (composites created from inputs of differing modalities, such as infrared and visible light radiation) is an important and growing area of research. Recent work has shown that the process of assessing fused images should not rely entirely on subjective quality methods, with objective tasks and computational metrics having important contributions to the assessment procedure. The current paper extends previous findings, applying a psychophysical selection task, metric evaluation, and subjective quality judgments to a range of fused surveillance images. Fusion schemes included the contrast pyramid and shift invariant discrete wavelet transform (Experiment 1), the complex wavelet transform (Experiments 1 & 2), and two false‐coloring methods (Experiment 2). In addition, JPEG2000 compression was applied at two levels, as well as an uncompressed control. Reaction time results showed the contrast pyramid to lead to slowest performance in the objective task, whilst the presence of color greatly reduced reaction times. These results differed from both the subjective and metric results. The findings support the view that subjective quality ratings should be used with caution, especially if not accompanied by some task.