A dynamic programming inspired outlier rejection algorithm for image mosaicing problem

Christopher Smith; Semih Dinc

doi:10.1117/12.2586955

4 January 2021 A dynamic programming inspired outlier rejection algorithm for image mosaicing problem

Christopher Smith, Semih Dinc

Proceedings Volume 11605, Thirteenth International Conference on Machine Vision; 1160514 (2021) https://doi.org/10.1117/12.2586955
Event: Thirteenth International Conference on Machine Vision, 2020, Rome, Italy

Abstract

Image mosaicing is a challenging problem when there is one (or more) corrupt image(s) in the input sequence. Since the transformation of later images rely on the previous transformation calculations, one miscalculation error caused by the corrupt image propagates to other image transformations, which fails the whole process. It is not a trivial task to detect and remove these corrupt images, which we call “outliers”. In this paper, we propose a dynamic programming inspired outlier rejection algorithm to identify and remove the corrupt image(s) from the sequence. Our approach stores the previously calculated transformation matrices in a 2D array and determines the validity of composite transformations based on a decision criterion. This criterion identifies the transformations coming from corrupt images by comparing the direct registration of images and the composite transformations from existing matrices in the array. We have performed experiments on both synthetic and real datasets. Visual and numerical results show that the proposed algorithm is an efficient tool for detecting and rejecting the outlier image from the mosaic image.

Citation Download Citation

Christopher Smith and Semih Dinc "A dynamic programming inspired outlier rejection algorithm for image mosaicing problem", Proc. SPIE 11605, Thirteenth International Conference on Machine Vision, 1160514 (4 January 2021); https://doi.org/10.1117/12.2586955

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