PIGUIQA: A Physical Imaging Guided Perceptual Framework for Underwater Image Quality Assessment
Journal:
arXiv
Published Date:
Dec 20, 2024
Abstract
In this paper, we propose a Physical Imaging Guided perceptual framework for
Underwater Image Quality Assessment (UIQA), termed PIGUIQA. First, we formulate
UIQA as a comprehensive problem that considers the combined effects of direct
transmission attenuation and backward scattering on image perception. By
leveraging underwater radiative transfer theory, we systematically integrate
physics-based imaging estimations to establish quantitative metrics for these
distortions. Second, recognizing spatial variations in image content
significance and human perceptual sensitivity to distortions, we design a
module built upon a neighborhood attention mechanism for local perception of
images. This module effectively captures subtle features in images, thereby
enhancing the adaptive perception of distortions on the basis of local
information. Third, by employing a global perceptual aggregator that further
integrates holistic image scene with underwater distortion information, the
proposed model accurately predicts image quality scores. Extensive experiments
across multiple benchmarks demonstrate that PIGUIQA achieves state-of-the-art
performance while maintaining robust cross-dataset generalizability. The
implementation is publicly available at
https://anonymous.4open.science/r/PIGUIQA-A465/
