Fast motion estimation using bidirectional gradient methods.

Yosi Keller; Amir Averbuch

doi:10.1109/tip.2004.823823

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PubMed · 15326846

Fast motion estimation using bidirectional gradient methods.

Yosi Keller·Amir Averbuch

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Abstract

Gradient-based motion estimation methods (GMs) are considered to be in the heart of state-of-the-art registration algorithms, being able to account for both pixel and subpixel registration and to handle various motion models (translation, rotation, affine, and projective). These methods estimate the motion between two images based on the local changes in the image intensities while assuming image smoothness. This paper offers two main contributions. The first is enhancement of the GM technique by introducing two new bidirectional formulations of the GM. These improve the convergence properties for large motions. The second is that we present an analytical convergence analysis of the GM and its properties. Experimental results demonstrate the applicability of these algorithms to real images.

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Algorithms Artifacts Data Compression Image Enhancement Image Interpretation, Computer-Assisted Motion Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted Subtraction Technique Video Recording Comparative Study Evaluation Study Journal Article Validation Study

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Yosi Keller, Amir Averbuch. 2004. Fast motion estimation using bidirectional gradient methods.. https://doi.org/10.1109/tip.2004.823823

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