An integrated architecture for adaptive image stabilization in zooming operation

Amanatiadis, Angelos; Andreadis, Ioannis

doi:10.1109/tce.2008.4560136

Cited by 16 publications

(2 citation statements)

References 42 publications

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“…This was necessary in order to minimize jitter and ensure correct priorization, especially under heavy load situations. Some of the performed image processing tasks were disparity estimation (Georgoulas et al (2008)), object tracking (Metta et al (2004)), image stabilization (Amanatiadis et al (2007)) and image zooming (Amanatiadis & Andreadis (2008)). For all these image processing cases, a careful selection of programming platform should be made.…”

Section: Software Architecturementioning

confidence: 99%

Stereo Vision System for Remotely Operated Robots

Amanatiadis¹,

Γαστεράτος²

2010

Remote and Telerobotics

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Section: Software Architecturementioning

confidence: 99%

Stereo Vision System for Remotely Operated Robots

Amanatiadis¹,

Γαστεράτος²

2010

Remote and Telerobotics

Self Cite

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“…Intelligent transportation systems equipped with vision systems use digital image stabilization for substantial reduction of the algorithm computational burden and complexity (Tyan et al (2004)), (Jin et al (2000)). Video communication systems with sophisticated compression codecs integrate image stabilization for improved computational and performance efficiency (Amanatiadis & Andreadis (2008)), (Chen et al (2007)). Furthermore, unwanted motion is removed from medical images via stabilization schemes (Zoroofi et al (1995)).…”

Section: Introductionmentioning

confidence: 99%

Image Stabilization in Active Robot Vision

Amanatiadis¹,

Γαστεράτος²,

Papadakis³

et al. 2010

Robot Vision

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Two‐dimensional adaptive Whittaker–Shannon Sinc‐based zooming

Ciulla,

Shabani,

Yahaya

2024

Applied Research

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In this work, we introduce a novel image zooming methodology that transitions from a nonadaptive Sin‐based approach to an adaptive Sinc‐based zooming technique. The two techniques base their theoretical foundation on the Whittaker–Shannon interpolation formula and the Nyquist theorem. The evolution into adaptive Sinc‐based zoom is accomplished through the use of two novel concepts: (1) the pixel‐local scaled k‐space and (2) the k‐space filtering sigmoidal function. The pixel‐local scaled k‐space is the standardized and scaled k‐space magnitude of the image to zoom. The k‐space filtering sigmoidal function scales the pixel‐local scaled k‐space values into the numerical interval [0, 1]. Using these two novel concepts, the Whittaker–Shannon interpolation formula is elaborated and used to zoom images. Zooming is determined by the shape of the Sinc functions in the Whittaker–Shannon interpolation formula, which, in turn, depends on the combined effect of the pixel‐local scaled k‐space, the sampling rate, and the k‐space filtering sigmoidal function. The primary outcome of this research demonstrates that the Whittaker–Shannon interpolation formula can achieve successful zooms for values of the sampling rate significantly greater than the bandwidth. Conversely, when the sampling rate is much greater than the bandwidth, the nonadaptive technique fails to perform the zoom correctly. The conclusion is that the k‐space filtering sigmoidal function is identified as the crucial parameter in the adaptive Sinc‐based zoom technique. The implications of this research extend to Sinc‐based image zooming applications.

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An integrated architecture for adaptive image stabilization in zooming operation

Abstract: Abstract

Cited by 16 publications

References 42 publications

Stereo Vision System for Remotely Operated Robots

Stereo Vision System for Remotely Operated Robots

Image Stabilization in Active Robot Vision

Two‐dimensional adaptive Whittaker–Shannon Sinc‐based zooming

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