Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150418
Title: Full-reference image quality assessment by combining features in spatial and frequency domains
Authors: Tang, Zhisen
Zheng, Yuanlin
Gu, Ke
Liao, Kaiyang
Wang, Wei
Yu, Miaomiao
Keywords: Engineering::Computer science and engineering
Issue Date: 2019
Source: Tang, Z., Zheng, Y., Gu, K., Liao, K., Wang, W. & Yu, M. (2019). Full-reference image quality assessment by combining features in spatial and frequency domains. IEEE Transactions On Broadcasting, 65(1), 138-151. https://dx.doi.org/10.1109/TBC.2018.2871376
Journal: IEEE Transactions on Broadcasting
Abstract: Objective image quality assessment employs mathematical and computational theory to objectively assess the quality of output images based on the human visual system (HVS). In this paper, a novel approach based on multifeature extraction in the spatial and frequency domains is proposed. We combine the gradient magnitude and phase congruency maps to generate a local structure (LS) map, which can perceive local structural distortions. The LS matches well with HVS and highlights differences with details. For complex visual information, such as texture and contrast sensitivity, we deploy the log-Gabor filter, and spatial frequency, respectively, to effectively capture their variations. Moreover, we employ the random forest (RF) to overcome the limitations of existing pooling methods. Compared with support vector regression, RF can obtain better prediction results. Extensive experimental results on the five benchmark databases indicate that the proposed method precedes all the state-of-the-art image quality assessment metrics in terms of prediction accuracy. In addition, the proposed method is in compliance with the subjective evaluations.
URI: https://hdl.handle.net/10356/150418
ISSN: 0018-9316
DOI: 10.1109/TBC.2018.2871376
Rights: © 2018 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

Page view(s)

130
Updated on Jun 30, 2022

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.