Paper
25 August 1992 Total least squares fitting spatiotemporal derivatives to smooth optical flow fields
Shenq Wang, Vishal Markandey, Anthony Reid
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Abstract
This paper investigates the application of total least squares (TLS) technique in conditioning optical flow field estimates obtained from gradient based optical flow constraints. Optical flow field processing has been applied to perform moving target indication (MTI) for IR/TV sensors but results can be severely degraded in noisy imagery. The usual solution is to apply some form of nonstatistical pre-processing to the input image intensities or statistical post- processing spatial smoothing, such as least squares (LS) fitting, to the output optical flow field vectors to suppress noise. However, LS solution is known for generating biased optical flow field vector estimate in noisy imagery due to spatial gradient matrix noise. Our empirical results show improved performance of TLS over LS at lower SNRs. Results are presented in terms of optical flow field accuracy measures and target detection rates, for synthetic imagery and real infrared imagery.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shenq Wang, Vishal Markandey, and Anthony Reid "Total least squares fitting spatiotemporal derivatives to smooth optical flow fields", Proc. SPIE 1698, Signal and Data Processing of Small Targets 1992, (25 August 1992); https://doi.org/10.1117/12.139397
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CITATIONS
Cited by 19 scholarly publications.
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KEYWORDS
Optical flow

Target detection

Sensors

Motion estimation

Detection and tracking algorithms

Motion measurement

Data processing

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