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Pyramidal Image Compression Using the Parameterized NEDI Algorithm

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Abstract

In the scope of pyramid image compression we offer the parameterization of NEDI-based interpolation algorithm. The original NEDI is an adaptive algorithm because it calculates the weight coefficients at each image point. The algorithm selects parameters that are best for the interpolation within the given vicinity of a particular pixel. The article proposes the parameterization of the NEDI algorithm which allows higher efficiency of the algorithm due to its better adaptiveness. Based on the evaluation of the intensity and direction of a local irregularity at each pixel, the parameterization makes it possible to simplify the structure of the interpolation algorithm and lessens its intricacy. The parameterized NEDI algorithm we offer is considered as a part of the pyramidal image compression method, which uses slightly thinned levels of the pyramidal representation to interpolate heavily thinned levels of the same pyramidal representation. Computational experiments prove that the use of the parameterized NEDI algorithm improves the efficiency of the pyramidal image compression method.

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Funding

The work was partly supported by the Russian Foundation for Basic Research, project no. 19-29-09045 (in parts 1, 2, 3), and the Ministry of Science and Higher Education of Russian Federation within the state project of FSRC “Crystallography and Photonics” RAS (in part “Introduction”).

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Authors and Affiliations

  1. Samara National Research University, Samara, Russia

    M. V. Gashnikov

  2. Image Processing Systems Institute, Russian Academy of Sciences—Branch of Crystallography and Photonics, Russian Academy of Sciences, 443001, Samara, Russia

    M. V. Gashnikov

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  1. M. V. Gashnikov
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Correspondence to M. V. Gashnikov.

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Gashnikov, M.V. Pyramidal Image Compression Using the Parameterized NEDI Algorithm. Opt. Mem. Neural Networks 30, 187–193 (2021). https://doi.org/10.3103/S1060992X21030036

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