Projects per year
In this paper, a novel and effective image quality assessment (IQA) algorithm based on frequency disparity for high dynamic range (HDR) images is proposed, termed as local-global frequency feature-based model (LGFM). Motivated by the assumption that the human visual system (HVS) is highly adapted for extracting structural information and partial frequencies when perceiving the visual scene, the Gabor and the Butterworth filters are applied to the luminance component of the HDR image to extract the local and global frequency features, respectively. The similarity measurement and feature pooling strategy are sequentially performed on the frequency features to obtain the predicted single quality score. The experiments evaluated on four widely used benchmarks demonstrate that the proposed LGFM can provide a higher consistency with the subjective perception compared with the state-of-the-art HDR IQA methods. Our code is available at: https://github.com/eezkni/LGFM.
|Number of pages||6|
|Journal||IEEE Transactions on Circuits and Systems for Video Technology|
|Early online date||19 Jan 2023|
|Publication status||Published - 1 Aug 2023|
Bibliographical noteFunding Information:
This work was supported in part by the Hong Kong Innovation and Technology Commission [InnoHK Project Centre for Intelligent Multidimensional Data Analysis (CIMDA)]; in part by the Hong Kong Research Grants Council (RGC) General Research Fund under Grant 11209819 (CityU 9042816), Grant 11203820 (CityU 9042598), and Grant 11203220 (CityU 9042957); in part by the Natural Science Foundation of China under Grant 62201387
© 1991-2012 IEEE.
- Butterworth feature
- Gabor feature
- Image quality assessment (IQA)
- high dynamic range (HDR)
FingerprintDive into the research topics of 'High Dynamic Range Image Quality Assessment Based on Frequency Disparity'. Together they form a unique fingerprint.
- 1 Active
KWONG, S. T. W., KUO, C. J., WANG, S. & ZHANG, X.
1/01/21 → 30/06/24
Project: Grant Research