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Image Quality Assessment Using Directional Anisotropy Structure Measurement.

Li Ding, Hua Huang, Yu Zang

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |February 11, 2017
    PubMed
    Summary

    This study introduces a new method, Directional Anisotropic Structure Measurement (DASM), to assess image quality by focusing on visually important structures. DASM effectively measures image degradation, correlating well with human perception.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Human Visual System (HVS) Modeling

    Background:

    • Image quality assessment relies on effective visual features.
    • Structure-based metrics approximate perceived distortion by measuring structural information change.
    • The Human Visual System (HVS) is more sensitive to distortions in dominant structures than textures.

    Purpose of the Study:

    • To develop a novel image quality assessment method by analyzing structural and textural behaviors.
    • To introduce a Directional Anisotropic Structure Measurement (DASM) that identifies visually dominant structures.

    Main Methods:

    • Analyzed psychovisual observations like anisotropy and local directionality.
    • Developed and applied the Directional Anisotropic Structure Measurement (DASM) as a visual feature.
    • Assessed image quality by measuring degradations using DASM.

    Main Results:

    • The proposed DASM effectively distinguishes dominant structures from minor textures.
    • The method demonstrated good performance across six benchmark databases.
    • Image quality assessment using DASM showed strong correlation with human perception.

    Conclusions:

    • DASM is a robust feature for image quality assessment, prioritizing visually significant structures.
    • The method aligns well with human visual perception of image quality.
    • This approach offers a more comprehensive analysis of image distortions.