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.
In a virtual environment (VE), efficient techniques are often needed to economize on rendering computation without compromising the information transmitted. The reported experiments devise a functional fidelity metric by exploiting research on memory schemata. According to the proposed measure, similar information would be transmitted across synthetic and real-world scenes depicting a specific schema. This would ultimately indicate which areas in a VE could be rendered in lower quality without affecting information uptake. We examine whether computationally more expensive scenes of greater visual fidelity affect memory performance after exposure to immersive VEs, or whether they are merely more aesthetically pleasing than their diminished visual quality counterparts. Results indicate that memory schemata function in VEs similar to real-world environments. "Highlevel" visual cognition related to late visual processing is unaffected by ubiquitous graphics manipulations such as polygon count and depth of shadow rendering; "normal" cognition operates as long as the scenes look acceptably realistic. However, when the overall realism of the scene is greatly reduced, such as in wireframe, then visual cognition becomes abnormal. Effects that distinguish schema-consistent from schema-inconsistent objects change because the whole scene now looks incongruent. We have shown that this effect is not due to a failure of basic recognition.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.