Edge-preserving MAP estimation of motion vector fields in noisy low-dose x-ray image sequences

Til Aach

doi:10.1117/12.323215

1 October 1998 Edge-preserving MAP estimation of motion vector fields in noisy low-dose x-ray image sequences

Til Aach

Proceedings Volume 3460, Applications of Digital Image Processing XXI; (1998) https://doi.org/10.1117/12.323215
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

We describe a motion compensated temporally recursive noise reduction technique especially suited for sequences of moving X-ray images, where we focus on a robust motion estimator which is able to deal with the high noise levels in such images. These noise levels are caused by the very low X-ray dose rates used in medical real-time imaging (quantum-limited imaging). The robustness of our motion estimator is achieved by spatiotemporal regularization using a generalized Gauss-Markov random field. Unlike quadratic regularization by Gauss-Markov random fields, generalized Gauss-Markov random fields are able to account for motion edges without the need to explicitly specify an detection threshold. Instead, our model controls edges by a `soft' parameter, which gradually allows the regularization term to behave like a median filter, which preserves edges without using detection thresholds.

Citation Download Citation

Til Aach "Edge-preserving MAP estimation of motion vector fields in noisy low-dose x-ray image sequences", Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); https://doi.org/10.1117/12.323215

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