Data-Driven Transform-Based Compressed Image Quality Assessment

Xinfeng ZHANG, Sam KWONG, C.-C. Jay KUO

Research output: Journal PublicationsJournal Article (refereed)peer-review

14 Citations (Scopus)

Abstract

Image quality assessment is a critical problem for image compression, which can be utilized as a guidance for image compression and codec evaluation. In this paper, we propose a full reference image quality assessment (IQA) algorithm to measure the perceptual quality of compressed images. The proposed IQA model utilizes a data-driven transform, multi-stage Karhunen-Loeve Transform (MS-KLT), as a feature extractor to decompose both reference and compressed images into feature domain, where the importance of feature distortions in different spectral components to human visual system (HVS) is easy to distinguish. Accordingly, an efficient weighting strategy is proposed to reflect the importance of feature distortions based on the energy of transformed coefficients. Considering HVS characteristics, weighted spatial masking effect is derived from both local and global perspectives. In addition, to avoid influences of random noises, a local adaptive low-pass filtering process is applied as a pre-processing operation. Extensive experimental results on popular datasets show that our proposed method correlates better with the subjective results compared with the state-of-the-art algorithms. Moreover, the proposed method behaves more robustly compared with existing methods, and achieves top-ranking performance on different IQA datasets.
Original languageEnglish
Pages (from-to)3352-3365
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume31
Issue number9
Early online date1 Dec 2020
DOIs
Publication statusPublished - Sept 2021
Externally publishedYes

Bibliographical note

This work was supported in part by the National Natural Science Foundation under Grant 62071449 and in part by the Research Start-Up Funds, University of Chinese Academy of Sciences.

Keywords

  • compressed image quality assessment
  • Data-driven transform
  • human visual system
  • KLT
  • visual masking

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