Comparing objective and subjective quality results for compression pre-processing with non-linear diffusion

  • Authors:
  • Ivan Kopilovic;Tamás Szirányi

  • Affiliations:
  • University of Konstanz, Department of Computer & Information Science, Konstanz, Germany;Analogical and Neural Computing Laboratory, Comp. & Automation Inst., Hungarian Academy of Sciences, Budapest, Hungary and University of Veszpréém, Department of Image Processing and Neu ...

  • Venue:
  • Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
  • Year:
  • 2003

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Abstract

Compression systems like JPEG include optional pre-processing with filtering to avoid compression artefacts. At higher compression ratios a stronger filtering is needed that impacts the large scale image content. To preserve the large scale information we have previously proposed to use non-linear diffusion as a pre-processing for filtering out small scale details irrelevant at a given compression ratio and acting as noise. Now we compare typical diffusion processes applied before the blockwise DCT compression using the peak signal to noise ration (PSNR) as an objective quality measure. We give a simple measure of artefact reduction in terms of PSNR, and show that a considerable artefact reduction is achieved by pre-processing at the same bit rate as and with no greater error than the original compression. We did tests to see if the above artefact reduction implies a better subjective impression of quality. The images processed with the PSNR-based algorithm had nearly the same but greater PSNR value as the original compression. Subjects preferred noisy image content to the lack of small scale details, so the subjective preference of the images with reduced artefact is worse that of the original compression. Results suggest however that non-linear diffusion is more efficient for artefact reduction than non-adaptive smoothing like Gaussian filtering in terms of the subjective preference.