BRIQA: Framework for the Blind and Referenced Visual Image Quality Assessment

Our proposal is to present a Blind and Referenced Image Quality Assessment or BRIQA. Thus, the main proposal of this paper is to propose an Interface, which contains not only a Full-Referenced Image Quality Assessment (IQA) but also a No- Referenced 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 BRIQA detects only one input, it performs a Blind Image Quality Assessment, on the contrary if BRIQA detects two inputs, it considers that a Referenced 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. BRIQA weights the Peak Signal-to-Noise Ratio by using an algorithm that estimates some properties of the Human Visual System. Then, we compare BRIQA algorithm not only with the mainstream estimator in IQA, PSNR, but also state-of-the-art IQA algorithms, such as Structural SIMilarity (SSIM), Mean Structural SIMilarity (MSSIM), Visual Information Fidelity (VIF), etc. Our experiments show that the correlation of BRIQA 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.

@article{Moreno2016,
  title     = {BRIQA: Framework for the Blind and Referenced Visual Image Quality Assessment},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {8},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Jaime Moreno and Oswaldo Morales and Ricardo Tejeida and Eduardo Garc´ia},
  doi       = {10.14569/IJACSA.2016.070842},
  url       = {https://doi.org/10.14569/IJACSA.2016.070842}
}