COMPRESSED IMAGE QUALITY ASSESSMENT BASED ON SAAK FEATURES

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

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

6 Citations (Scopus)

Abstract

Compressed image quality assessment plays an important role in image services, especially in image compression applications, which can be utilized as a guidance to optimize image processing algorithms. In this paper, we propose an objective image quality assessment algorithm to measure the quality of compressed images. The proposed method utilizes a data-driven transform, Saak (Subspace approximation with augmented kernels), to decompose images into hierarchical structural feature space. We measure the distortions of Saak features and accumulate these distortions according to the feature importance to human visual system. Compared with the state-of-the-art image quality assessment methods on widely utilized datasets, the proposed method correlates better with the subjective results. In addition, the proposed methods achieves more robust results on different datasets.
Original languageEnglish
Title of host publicationProceedings - International Conference on Image Processing, ICIP
Pages1730-1734
DOIs
Publication statusPublished - Sept 2019
Externally publishedYes

Keywords

  • compressed image
  • HVS
  • image quality assessment
  • Saak
  • structural distortion

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