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Research Article | Open Access

Discernible image mosaic with edge-aware adaptive tiles

College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong, China.
School of Computing Science, Simon Fraser University, Vancouver, BC, Canada.
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Abstract

We present a novel method to produce discernible image mosaics, with relatively large image tiles replaced by images drawn from a database, to resemble a target image. Compared to existing works on image mosaics, the novelty of our method is two-fold. Firstly, believing that the presence of visual edges in the final image mosaic strongly supports image perception, we develop an edge-aware photo retrieval scheme which emphasizes the preservation of visual edges in the target image. Secondly, unlike most previous works which apply a pre-determined partition to an input image, our image mosaics are composed of adaptive tiles, whose sizes are determined based on the available images in the database and the objective of maximizing resemblance to the target image. We show discernible image mosaics obtained by our method, using image collections of only moderate size. To evaluate our method, we conducted a user study to validate that the image mosaics generated present both globally and locally appropriate visual impressions to the human observers. Visual comparisons with existing techniques demonstrate the superiority of our method in terms of mosaic quality and perceptibility.

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Computational Visual Media
Pages 45-58

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Cite this article:
Xu P, Ding J, Zhang H, et al. Discernible image mosaic with edge-aware adaptive tiles. Computational Visual Media, 2019, 5(1): 45-58. https://doi.org/10.1007/s41095-019-0130-7

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Revised: 09 December 2018
Accepted: 20 January 2019
Published: 08 April 2019
© The author(s) 2019

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduc-tion in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

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Other papers from this open access journal are available free of charge from http://www.springer.com/journal/41095. To submit a manuscript, please go to https://www.editorialmanager.com/cvmj.