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  • Open Access

    ARTICLE

    Super-Resolution Based on Curvelet Transform and Sparse Representation

    Israa Ismail1,*, Mohamed Meselhy Eltoukhy1,2, Ghada Eltaweel1

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 167-181, 2023, DOI:10.32604/csse.2023.028906 - 16 August 2022

    Abstract Super-resolution techniques are used to reconstruct an image with a high resolution from one or more low-resolution image(s). In this paper, we proposed a single image super-resolution algorithm. It uses the nonlocal mean filter as a prior step to produce a denoised image. The proposed algorithm is based on curvelet transform. It converts the denoised image into low and high frequencies (sub-bands). Then we applied a multi-dimensional interpolation called Lancozos interpolation over both sub-bands. In parallel, we applied sparse representation with over complete dictionary for the denoised image. The proposed algorithm then combines the dictionary More >

  • Open Access

    ARTICLE

    Applying Non-Local Means Filter on Seismic Exploration

    Mustafa Youldash1, Saleh Al-Dossary2,*, Lama AlDaej1, Farah AlOtaibi1, Asma AlDubaikil1, Noora AlBinali1, Maha AlGhamdi1

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 619-628, 2022, DOI:10.32604/csse.2022.017733 - 09 September 2021

    Abstract The seismic reflection method is one of the most important methods in geophysical exploration. There are three stages in a seismic exploration survey: acquisition, processing, and interpretation. This paper focuses on a pre-processing tool, the Non-Local Means (NLM) filter algorithm, which is a powerful technique that can significantly suppress noise in seismic data. However, the domain of the NLM algorithm is the whole dataset and 3D seismic data being very large, often exceeding one terabyte (TB), it is impossible to store all the data in Random Access Memory (RAM). Furthermore, the NLM filter would require More >

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