An image coding/decoding method based on direct and inverse fuzzy transforms

  • Authors:
  • Ferdinando Di Martino;Vincenzo Loia;Irina Perfilieva;Salvatore Sessa

  • Affiliations:
  • Università degli Studi di Napoli “Federico II”, Dipartimento di Costruzioni e Metodi Matematici in Architettura, Via Monteoliveto 3, 80134 Napoli, Italy and Università degli ...;Università degli Studi di Salerno, Dipartimento di Matematica e Informatica, Via Ponte Don Melillo, 84084 Fisciano (Salerno), Italy;University of Ostrava, Institute for Research and Applications of Fuzzy Modeling, 70103 Ostrava 1, Czech Republic;Università degli Studi di Napoli “Federico II”, Dipartimento di Costruzioni e Metodi Matematici in Architettura, Via Monteoliveto 3, 80134 Napoli, Italy

  • Venue:
  • International Journal of Approximate Reasoning
  • Year:
  • 2008

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Abstract

With some modifications, we adopt the coding/decoding method of image processing based on the direct and inverse fuzzy transforms defined in previous papers. By normalizing the values of its pixels, any image can be considered as a fuzzy matrix (relation) which is subdivided in submatrices (possibly square) called blocks. Each block is compressed with the formula of the discrete fuzzy transform of a function in two variables and successively it is decompressed via the related inverse fuzzy transform. The decompressed blocks are recomposed for the reconstruction of the image, whose quality is evaluated by calculating the PSNR (Peak Signal to Noise Ratio) with respect to the original image. A comparison with the coding/decoding method of image processing based on the fuzzy relation equations with the Lukasiewicz triangular norm and the DCT method are also presented. By using the same compression rate in the three methods, the results show that the PSNR obtained with the usage of direct and inverse fuzzy transforms is higher than the PSNR determined either with fuzzy relation equations method or in the DCT one and it is close to the PSNR determined in JPEG method for small values of the compression rate.