CB p F -IQA: Using contrast band-pass filtering as main axis of visual image quality assessment

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    Our proposal is to present a Blind and Reference Image Quality Assessment or CBPF-IQA. Thus, the main proposal of this paper is to propose an Interface, which contains not only a Full-Reference Image Quality Assessment (IQA) but also a No-Reference or Blind IQA applying perceptual concepts by means of Contrast Band-Pass Filtering (CBPF). Then, this proposal consists, in contrast, a degraded input image with the filtered versions of several distances by a CBPF, which computes some of the Human Visual System (HVS) variables. If CBPF-IQA detects only one input, it performs a Blind Image Quality Assessment, on the contrary, if CBPF-IQA detects two inputs, it considers that a Reference Image Quality Assessment will be computed. Thus, we first define a Full-Reference IQA and then a No-Reference IQA, which correlation is important when is contrasted with the psychophysical results performed by several observers. CBPF-IQA weights the Peak Signal-to-Noise Ratio by using an algorithm that estimates some properties of the Human Visual System. Then, we compare CB p F -IQA algorithm not only with the mainstream estimator in IQA and PSNR but also state-of-the-art IQA algorithms, such as Structural SIMilarity (SSIM), Mean Structural SIMilarity (MSSIM), and Visual Information Fidelity (VIF). Our experiments show that the correlation of CBPF-IQA correlated with PSNR is important, but this proposal does not need imperatively the reference image in order to estimate the quality of the recovered image.

    Idioma originalInglés
    Título de la publicación alojadaStudies in Computational Intelligence
    EditorialSpringer Verlag
    Número de páginas22
    EstadoPublicada - 1 ene 2018

    Serie de la publicación

    NombreStudies in Computational Intelligence
    ISSN (versión impresa)1860-949X


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