A two-state switched-median filter

Badulescu, P.; Zacin, R.

doi:10.1109/smicnd.2000.890238

2000 International Semiconductor Conference. 23rd Edition. CAS 2000 Proceedings (Cat. No.00TH8486)

DOI: 10.1109/smicnd.2000.890238

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A two-state switched-median filter

P. Badulescu

R. Zacin²

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A system and method for auto-correction of first order lens distortion

Fry

Pusateri

2010

2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)

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In multispectral imaging systems, correction for lens distortion is required to allow pixel by pixel fusion techniques to be applied. While correction of optical aberration can be extended to higher order terms, for many systems, a first order correction is sufficient to achieve desired results. In producing a multispectral imaging system in production quantities, the process of producing the corrections needs to be largely automated as each lens will require its own corrections.We discuss an auto-correction and bench sighting method application to a dual band imaging system. In principle, we wish to image a dual band target and completely determine the lens distortion parameters for the given optics. We begin with a scalepreserving, radial, first-order lens distortion model; this model allows the horizontal field of view to be determined independently of the distortion. It has the benefits of simple parameterization and the ability to correct mild to moderate distortion that may be expected of production optics. The correction process starts with imaging a dual band target. A feature extraction algorithm is applied to the imagery from both bands to generate a large number of correlated feature points. Using the feature points, we derive an over-determined system of equations; the solution to this system yields the distortion parameters for the lens. Using these parameters, an interpolation map can be generated unique to the lenses involved. The interpolation map is used in real-time to correct the distortion while preserving the horizontal field of view constraint on the system.

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A system and method for auto-correction of first order lens distortion

Fry

Pusateri

2010

2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)

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Real-time adaptive pixel replacement

Pusateri

Scott²,

Mushtaq³

2010

2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)

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High probability impulsive noise removal for corrupted images

Hsiao

Chen

2004

24th International Conference on Distributed Computing Systems Workshops, 2004. Proceedings.

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We know one characteristic of image is that each pixel is very close to surrounding neighbors. If the impulsive noise appears in the local area, it will be very abruptly. In the proposed scheme, we pick up several neighboring pixels around the center pixel in the scanning window as the statistic factors. The mean value and mean of absolute neighboring difference (MAND) are utilized from those. Further, we use them to acquire a critical value. The value is a representative characteristic of those pixels in the local area and it will be used to identify whether if a pixel is corrupted.

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A two-state switched-median filter

Cited by 3 publications

References 2 publications

A system and method for auto-correction of first order lens distortion

A system and method for auto-correction of first order lens distortion

Real-time adaptive pixel replacement

High probability impulsive noise removal for corrupted images

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