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Spline-Based Dense Medial Descriptors for Image Simplification Using Saliency Maps

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Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1691))

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Abstract

Medial descriptors have attracted increasing interest in image representation, simplification, and compression. Recently, such descriptors have been separately used to (a) increase the local quality of representing salient features in an image and (b) globally compress an entire image via a B-spline encoding. To date, the two desiderates, (a) high local quality and (b) high overall compression of images, have not been addressed by a single medial method. We achieve this integration by presenting Spatial Saliency Spline Dense Medial Descriptors (3S-DMD) for saliency-aware image simplification-and-compression. Our method significantly improves the trade-off between compression and image quality of earlier medial-based methods while kee** perceptually salient features. We also demonstrate the added-value of user-designed, as compared to automatically-computed, saliency maps. We show that our method achieves both higher compression and better quality than JPEG for a broad range of images and, for specific image types, yields higher compression and similar quality than JPEG 2000.

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Acknowledgments

The first author acknowledges the China Scholarship Council (Grant number: 201806320354) for financial support.

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Authors and Affiliations

  1. Bernoulli Institute, University of Groningen, 9747 AG, Groningen, The Netherlands

    Jiří Kosinka

  2. Department of Information Systems, Institute of Computing, University of Campinas, São Paulo, 13083-852, Brazil

    Leonardo de Melo & Alexandre X. Falcão

  3. Department of Information and Computing Sciences, Utrecht University, 3584 CC, Utrecht, The Netherlands

    Alexandru Telea

  4. Bernoulli Institute, Shandong University of Science and Technology, 579 Qianwangang Road, Huangdao District, Qingdao, 266590, Shandong Province, P.R. China

    Jieying Wang

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  1. Jieying Wang
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  2. Leonardo de Melo
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  4. Jiří Kosinka
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  5. Alexandru Telea
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Corresponding author

Correspondence to Jieying Wang .

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Editors and Affiliations

  1. University of Porto, Porto, Portugal

    A. Augusto de Sousa

  2. Czech Technical University in Prague, Prague, Czech Republic

    Vlastimil Havran

  3. Mines ParisTech, Paris, France

    Alexis Paljic

  4. Davidson College, Davidson, NC, USA

    Tabitha Peck

  5. French Civil Aviation University (ENAC), Toulouse, France

    Christophe Hurter

  6. Monash University, Melbourne, Australia

    Helen Purchase

  7. University of Catania, Catania, Italy

    Giovanni Maria Farinella

  8. University of Barcelona, Barcelona, Spain

    Petia Radeva

  9. IRISA, University of Rennes 1, Rennes, France

    Kadi Bouatouch

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Wang, J., Melo, L.d., Falcão, A.X., Kosinka, J., Telea, A. (2023). Spline-Based Dense Medial Descriptors for Image Simplification Using Saliency Maps. In: de Sousa, A.A., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2021. Communications in Computer and Information Science, vol 1691. Springer, Cham. https://doi.org/10.1007/978-3-031-25477-2_13

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  • DOI: https://doi.org/10.1007/978-3-031-25477-2_13

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