TY - GEN
T1 - No-Reference Image Sharpness Assessment Based on Perceptually-Weighted Image Gradients
AU - Andrade, Juan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The fact that human visual perception is highly spe-cialized for extracting structural information has been efficiently exploited in full-reference image quality assessment algorithms; additionally, it has been shown that the human perception of sharpness depends on the local image contrast. Since the image gradients can measure effectively the image structure, we propose a training-free no-reference objective image sharpness assessment method based on the statistical analysis of perceptually-weighted normalized -gradients of relevant pixels in the input image. Results over six subject-rated publicly available databases show that the proposed no-reference sharpness assessment algorithm correlates well with perceived sharpness and provides competitive performance when compared with state-of-the-art algorithms despite its low computational burden.
AB - The fact that human visual perception is highly spe-cialized for extracting structural information has been efficiently exploited in full-reference image quality assessment algorithms; additionally, it has been shown that the human perception of sharpness depends on the local image contrast. Since the image gradients can measure effectively the image structure, we propose a training-free no-reference objective image sharpness assessment method based on the statistical analysis of perceptually-weighted normalized -gradients of relevant pixels in the input image. Results over six subject-rated publicly available databases show that the proposed no-reference sharpness assessment algorithm correlates well with perceived sharpness and provides competitive performance when compared with state-of-the-art algorithms despite its low computational burden.
KW - Image blur
KW - Image sharpness
KW - No-reference image quality assessment
KW - Objective blur assessment
KW - Perceptual-based
KW - Image blur
KW - Image sharpness
KW - No-reference image quality assessment
KW - Objective blur assessment
KW - Perceptual-based
UR - https://link.springer.com/chapter/10.1007/978-3-319-73432-3_5
U2 - 10.1109/IISA59645.2023.10345886
DO - 10.1109/IISA59645.2023.10345886
M3 - Contribución a la conferencia
T3 - 14th International Conference on Information, Intelligence, Systems and Applications, IISA 2023
BT - 14th International Conference on Information, Intelligence, Systems and Applications, IISA 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Conference on Information, Intelligence, Systems and Applications, IISA 2023
Y2 - 10 July 2023 through 12 July 2023
ER -