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)


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 : 2019 IEEE International Conference on Image Processing
Number of pages5
ISBN (Electronic)9781538662496
ISBN (Print)9781538662502
Publication statusPublished - Sept 2019
Externally publishedYes
Event26th IEEE International Conference on Image Processing (ICIP 2019) - Taipei International Convention Center (TICC), Taipei, Taiwan, Province of China
Duration: 22 Sept 201925 Sept 2019


Conference26th IEEE International Conference on Image Processing (ICIP 2019)
Country/TerritoryTaiwan, Province of China
Internet address


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


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