Scene-dependent harmonization of aircraft vision systems

Lambert, Ben; Ralph, Jason F.; Sims, Scott W.; Wren, Lee; Dwyer, David

doi:10.1117/12.541496

Cited by 2 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It may also show up as a gradual drop in the determinant of the matrix in (4). If situations such as these occur, further filtering is applied to minimise any effect this may have on the output.…”

Section: Registration and Harmonisation Of Synthetic Imagerymentioning

confidence: 96%

“…There is a significant amount of literature available on this subject 2,3 , in which many techniques and approaches have been used. The previous paper 4 , mainly concentrated on the situation where multiple sensors are distributed across an airframe, as per suggestions for inclusion in a Distributed Aperture InfraRed System (DAIRS) 5 for future high-speed jets. The idea behind DAIRS 6 is to replace conventional gimballed sensors with a number of fixed staring sensors, and to achieve this automated algorithms to align or harmonise the imagery from different cameras are required.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Harmonization and alignment of multiple camera imagery

Lambert

Ralph

Wren

et al. 2005

Signal Processing, Sensor Fusion, and Target Recognition XIV

Self Cite

View full text Add to dashboard Cite

Multiple camera systems have been considered for a number of applications, including infrared (IR) missile detection in modern fast jet aircraft, and soldier-aiding data fusion systems. This paper details experimental work undertaken to test image-processing and harmonisation techniques that were developed to align multiple camera systems. This paper considers systems where the camera properties are significantly different and the camera fields of view do not necessarily overlap. This is in contrast to stereo calibration alignment techniques that rely on similar resolution, fields of view and overlapping imagery. Testing has involved the use of two visible-band cameras and attempts to harmonise a narrow field of view camera with a wide field of view camera. In this paper, consideration has also been given to the applicability of the algorithms to both visual-band and IR based camera systems, the use of supplementary motion information from inertial measurement systems and consequent system limitations.

show abstract

Section: Registration and Harmonisation Of Synthetic Imagerymentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Harmonization and alignment of multiple camera imagery

Lambert

Ralph

Wren

et al. 2005

Signal Processing, Sensor Fusion, and Target Recognition XIV

Self Cite

View full text Add to dashboard Cite

show abstract

“…Whilst the alignment techniques described in this paper are quite general -and similar techniques have been applied to visible band cameras/imagery [3] -the main application under consideration is for infrared imaging and the alignment of infrared imagers from sequences of imagery. There are several problems associated with infrared imaging that make the identification of the optical flow field quite difficult.…”

Section: Image Registration and Rotationsmentioning

confidence: 99%

“…If the cameras are pointing in different directions, deriving the rotations that allow the invariant axes to be lined up is equivalent to finding their relative orientations. In practice, the estimation of the invariant axes will be affected by noise in the optical flow field and associated transformations, so the estimation of the relative orientation of the cameras requires the use of a Kalman or other suitable filter to obtain a good estimate of the relative rotation [3]. This paper describes the basic theory and gives examples of its use.…”

Section: Introductionmentioning

confidence: 98%

“…This is at the heart of the process of egomotion estimation [2], the general term applied to the extraction of camera motion from images. This paper deals with a specific application of ego-motion estimation, that of aligning two cameras even when they have very different, nonoverlapping fields of view [3]. The technique uses the optical flow field generated by the motion of each camera to find a 3D rotational transformation from image frame to image frame, and then finds an axis (in the three-dimensional camera axes) which is invariant to this transformation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spherical alignment of imagers using optical flow fields

Lambert

Ralph

Wren

et al. 2006

Acquisition, Tracking, and Pointing XX

Self Cite

View full text Add to dashboard Cite

Optical flow fields can be used to recover some components of the camera ego-motion such as velocity and angular velocity. In this paper, we discuss the use of optical flow fields to estimate the relative orientation of two imagers with non-overlapping fields of view. The algorithms proposed are based on a spherical alignment technique which is closely related to rapid transfer alignment methods used to align aircraft inertial navigation systems. Of particular importance is the relationship between the accuracy of the optical flow field (which is dependent upon the complexity of the scene and the resolution of the cameras) and the accuracy of the resultant alignment process.

show abstract

Scene-dependent harmonization of aircraft vision systems

Cited by 2 publications

References 0 publications

Harmonization and alignment of multiple camera imagery

Harmonization and alignment of multiple camera imagery

Spherical alignment of imagers using optical flow fields

Contact Info

Product

Resources

About