Multimodal image registration with applications to image fusion

Heather, J.P.; Smith, Moira I.

doi:10.1109/icif.2005.1591879

Cited by 23 publications

(30 citation statements)

References 8 publications

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“…Thorough reviews of image registration methods can be found in [21,[37][38][39][40][41][42]. Registration approaches that work in real time on live imagery are discussed by Heather and Smith [43].…”

Section: Role Of Image Registrationmentioning

confidence: 99%

Image fusion: Advances in the state of the art

2007

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Section: Role Of Image Registrationmentioning

confidence: 99%

Image fusion: Advances in the state of the art

2007

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“…Image registration is the process of spatially aligning two or more images of the same scene, possibly recorded at different moments in time (Heather and Smith 2005) or acquired using different sensors. Fundamentally, the pixel registration problem can be presented as a mapping problem between the pixels (x,y) from the first source image, and the (u,v) from the other, as described in Eq.…”

Section: Preprocessingmentioning

confidence: 99%

Pixel-Level Fusion for Infrared and Visible Acquisitions

Zhou

Omar

2009

International Journal of Optomechatronics

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This article presents a unique combined routine to fuse Long Wave Infrared (7.5-13 micron) with visible (0.38-0.78 micron) acquisitions, and to track pedestrians and road information in night or low light driving scenarios. Three fusion levels are presented and discussed: pixellevel, feature-level and decision-level. A pixel-level fusion is then used, through a novel combination of an adaptive weighting algorithm for un-saturated data points, and a PCA statistics for saturated pixels. The registration is done at the hardware level with Gaussian smoothing, while the smoothed histograms provide initial threshold values. The proposed routine is then applied for different night-time driving scenarios, further compared with the tracking results for non-fused thermal imagery from a commercial night-vision module. The fused imagery coupled with the proposed pre and post-processing provide complete detection of reflective and emitting objects with better shape retrieval and orientation prediction, computed and judged through objects morphology. The result of current work is an enhanced passive display for: passing vehicles with glare, pedestrians and non-emitting road features, with its motion predicted.

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“…Heather and Smith [7] introduced a multimodal image registration algorithm for image fusion. The unregistered images captured in short distance in above two algorithms.…”

Section: Introductionmentioning

confidence: 99%

An automatic registration method based on runway detection

Zhang

Guo

2014

SPIE Proceedings

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Runway is seen distinctly that is a crucial condition in the process of approaching and landing. One of the enhanced vision methods is image fusion method between the infrared and visible images in EVS (Enhanced Vision System). The image registration plays a very important role in image fusion. So, an automatic image registration method is proposed based on the accurate runway detection. Firstly, runway is detected using DWT (discrete wavelets transform) from the infrared and visible images respectively. Then, a fitting triangle is constructed according to the edges of runway. The corresponding feature points extracted from the middle points of edges and the centroid of triangle are used to compute the transform parameters. The results of registration are more accurate and efficient than those of registration based on mutual information. This method is robust and has less computation which can be applied to real-time system.

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Multimodal image registration with applications to image fusion

Cited by 23 publications

References 8 publications

Image fusion: Advances in the state of the art

Image fusion: Advances in the state of the art

Pixel-Level Fusion for Infrared and Visible Acquisitions

An automatic registration method based on runway detection

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