TY - JOUR
T1 - Defining a no-reference image quality assessment by means of the self-affine analysis
AU - Escobar, Jesús Jaime Moreno
AU - Matamoros, Oswaldo Morales
AU - Reyes, Ixchel Lina
AU - Padilla, Ricardo Tejeida
AU - Hernández, Liliana Chanona
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.
PY - 2021/4
Y1 - 2021/4
N2 - In this paper we propose a novel Blind Image Quality Assessment via Self-Affine Analysis (BIQSAA) method by considering the wavelet transform as a linear operation that decomposes a complex signal into elementary blocks at different scales or resolutions. BIQSAA decomposes a distorted image into a set of wavelet planes ωλ, ϕ of different spatial frequencies λ and spatial orientations ϕ, and it transforms these wavelet planes into one-dimension vector Ω using a Hilbert scanning. From the vector Ω there were obtained their wavelet coefficient fluctuations estimated by the inverse of the Hurst exponent in decibels, whose scaling-law or fractal behavior was obtained by applying Fractal Geometry or Self-Affine Analysis. The scaling exponents calculated for the coefficient fluctuation behavior of Image Lena at 24bpp, at 1.375bpp, and at 0.50bpp were H24bpp = 0.0395, H1.375bpp = 0.0551, and H0.50bpp = 0.0612, respectively. Our experiments show that BIQSAA algorithm improves in 14.36% the Human Visual System correlation, respect to the four state-of-the-art No-Reference Image Quality Assessments.
AB - In this paper we propose a novel Blind Image Quality Assessment via Self-Affine Analysis (BIQSAA) method by considering the wavelet transform as a linear operation that decomposes a complex signal into elementary blocks at different scales or resolutions. BIQSAA decomposes a distorted image into a set of wavelet planes ωλ, ϕ of different spatial frequencies λ and spatial orientations ϕ, and it transforms these wavelet planes into one-dimension vector Ω using a Hilbert scanning. From the vector Ω there were obtained their wavelet coefficient fluctuations estimated by the inverse of the Hurst exponent in decibels, whose scaling-law or fractal behavior was obtained by applying Fractal Geometry or Self-Affine Analysis. The scaling exponents calculated for the coefficient fluctuation behavior of Image Lena at 24bpp, at 1.375bpp, and at 0.50bpp were H24bpp = 0.0395, H1.375bpp = 0.0551, and H0.50bpp = 0.0612, respectively. Our experiments show that BIQSAA algorithm improves in 14.36% the Human Visual System correlation, respect to the four state-of-the-art No-Reference Image Quality Assessments.
KW - Image quality assessment
KW - Self-affine analysis
KW - Signal processing
KW - Wavelet transform
UR - http://www.scopus.com/inward/record.url?scp=85099762704&partnerID=8YFLogxK
U2 - 10.1007/s11042-020-10245-5
DO - 10.1007/s11042-020-10245-5
M3 - Artículo
C2 - 33500679
AN - SCOPUS:85099762704
SN - 1380-7501
VL - 80
SP - 14305
EP - 14320
JO - Multimedia Tools and Applications
JF - Multimedia Tools and Applications
IS - 9
ER -