Exploiting tensor-space similarity measures in image and video processing

  • Authors

    • Adib Akl Holy Spirit University of Kaslik
    • Charles Yaacoub Holy Spirit University of Kaslik
    https://doi.org/10.14419/ijet.v7i4.12700

    Received date: May 10, 2018

    Accepted date: December 3, 2018

    Published date: March 22, 2019

  • Gradient Fields, Image Analysis, Local Structures, Motion Estimation, Similarity Measure, Structure Tensor.

  • Abstract

    Measuring the similarity between images is a crucial process for several image and video processing applications. For instance, it is used in image inpainting, image retrieval, pattern recognition, as well as image and video compression. Traditional intensity-based approaches have shown efficiency in different situations and scenarios. However, failures still exist, especially in the case of high local structural variation images. In this paper, different tensor-based metrics that reveal the local structural information are presented and evaluated in several dissimilarity estimation contexts. Results show that using these metrics, relevant dissimilarities of local patterns can be better detected, thus helping standard intensity-based image inpainting algorithms, motion estimation methods and the analysis of medical images.

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  • How to Cite

    Akl, A., & Yaacoub, C. (2019). Exploiting tensor-space similarity measures in image and video processing. International Journal of Engineering and Technology, 7(4), 5196-5205. https://doi.org/10.14419/ijet.v7i4.12700