• DocumentCode
    3044977
  • Title

    Homogeneity Based Blind Noisy Image Quality Assessment

  • Author

    Xiaotong Huang ; Li Chen ; Jing Tian ; Xiaolong Zhang ; Xiaowei Fu

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Wuhan Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2013
  • fDate
    13-16 Oct. 2013
  • Firstpage
    2963
  • Lastpage
    2967
  • Abstract
    Blind noisy image quality assessment aims to evaluate the quality of the degraded noisy image without the need for the ground truth image. To tackle this challenge, this paper proposes an image quality assessment approach using block homogeneity. The contribution of the proposed approach is two-fold. First, a block-based homogeneity measure is proposed to estimate the statistics (e.g., variance) of the noise incurred in the image, based on adaptively selected homogeneous image regions. Second, an image quality assessment approach is proposed by exploiting the above-mentioned estimated noise variance, along with the visual masking effect of the human visual system. Experimental results are provided to demonstrate that the proposed image noise estimation approach yields superior accuracy and stability performance to that of conventional approaches, and the proposed image quality assessment approach achieves consistent performance to that of human subjective evaluation.
  • Keywords
    estimation theory; image denoising; adaptively selected homogeneous image regions; block homogeneity; block-based homogeneity measure; ground truth image; homogeneity based blind noisy image quality assessment; human subjective evaluation; human visual system; image noise estimation; noise variance; stability performance; visual masking effect; Estimation error; Image quality; Noise; Noise level; Noise measurement; blind image quality assessment; block homogeneity; image noise estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
  • Conference_Location
    Manchester
  • Type

    conf

  • DOI
    10.1109/SMC.2013.505
  • Filename
    6722258