Visual Computing

University of Konstanz
Journal of Visual Communication and Image Representation

No-reference Quality Assessment for DCT-based Compressed Image

C. Wang, M. Shen, C. Yao

Abstract

A blind/no-reference (NR) method is proposed in this paper for image quality assessment (IQA) of the images compressed in discrete cosine transform (DCT) domain. When an image is measured by structural similarity (SSIM), two variances, i.e. mean intensity and variance of the image, are used as features. However, the parameters of original copies are actually unavailable in NR applications; hence SSIM is not widely applicable. To extend SSIM in general cases, we apply Gaussian model to fit quantization noise in spatial domain, and directly estimate noise distribution from the compressed version. Benefit from this rearrangement, the revised SSIM does not require original image as the reference. Heavy compression always results in some zero-value DCT coefficients, which need to be compensated for more accurate parameter estimate. By studying the quantization process, a machine-learning based algorithm is proposed to estimate quantization noise taking image content into consideration. Compared with state-of-the-art algorithms, the proposed IQA is more heuristic and efficient. With some experimental results, we verify that the proposed algorithm (provided no reference image) achieves comparable efficacy to some full reference (FR) methods (provided the reference image), such as SSIM.

BibTeX

@article{Wang2015NoreferenceQuality,
  acmid      = {2803980},
  address    = {Orlando, FL, USA},
  author     = {C. Wang and M. Shen and C. Yao},
  doi        = {10.1016/j.jvcir.2015.01.006},
  issn       = {1047-3203},
  issue_date = {April 2015},
  journal    = {Journal of Visual Communication and Image Representation},
  keywords   = {Compression distortion, Gaussian distribution, Image quality assessment, No-reference estimate, Noise variance, Objective quality assessment, Probability model, Uniform distribution},
  month      = {apr},
  number     = {C},
  numpages   = {7},
  pages      = {53--59},
  publisher  = {Academic Press, Inc.},
  title      = {No-reference Quality Assessment for DCT-based Compressed Image},
  volume     = {28},
  year       = {2015},
}

Supplemental Material

Paper (.pdf, 619.1 KB)