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An analysis on the effect of image features on lossy coding performance

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2 Author(s)
Saha, S. ; California Univ., Davis, CA, USA ; Vemuri, R.

When a variety of multimedia images of different types (natural, synthetic, compound, medical, etc.) are compressed using a fixed wavelet filter, it is observed that the peak SNR (PSNR) values for a given compression ratio vary widely by as much as 30 dB from image to image. In this letter, it is shown that most of the gray-level histogram statistics of the images do not have any direct effect on the lossy coding performance, and image activity measure (IAM) is the only feature that has a negative correlation with the PSNR value. We determine the best measure of such image activity and show that one of these IAMs is not only very effective in differentiating between various images but also correlates well with the PSNR. We establish this relationship in the form of the IAM-PSNR equation.

Published in:

Signal Processing Letters, IEEE  (Volume:7 ,  Issue: 5 )