No-Reference Image Sharpness Assessment Based on Perceptually-Weighted Image Gradients

Juan Andrade

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

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.

Idioma originalInglés
Título de la publicación alojada14th International Conference on Information, Intelligence, Systems and Applications, IISA 2023
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9798350318067
DOI
EstadoPublicada - 2023
Evento14th International Conference on Information, Intelligence, Systems and Applications, IISA 2023 - Volos, Grecia
Duración: 10 jul. 202312 jul. 2023

Serie de la publicación

Nombre14th International Conference on Information, Intelligence, Systems and Applications, IISA 2023

Conferencia

Conferencia14th International Conference on Information, Intelligence, Systems and Applications, IISA 2023
País/TerritorioGrecia
CiudadVolos
Período10/07/2312/07/23

Palabras clave

  • Image blur
  • Image sharpness
  • No-reference image quality assessment
  • Objective blur assessment
  • Perceptual-based

Huella

Profundice en los temas de investigación de 'No-Reference Image Sharpness Assessment Based on Perceptually-Weighted Image Gradients'. En conjunto forman una huella única.

Citar esto