wEscore: quality assessment method of multichannel image visualization with regard to angular resolution

Abstract

This work considers the problem of quality assessment of multichannel image visualization methods. One approach to such an assessment, the Escore quality measure, is studied. This measure, initially proposed for decolorization methods evaluation, can be generalized for the assessment of hyperspectral image visualization methods. It is shown that Escore does not account for the loss of local contrast at the supra-pixel scale. The sensitivity to the latter in humans depends on the observation conditions, so we propose a modified wEscore measure which includes the parameters allowing for the adjustment of the local contrast scale based on the angular resolution of the images. We also describe the adjustment of wEscore parameters for the evaluation of known decolorization algorithms applied to the images from the COLOR250 and the Cadik datasets with given observational conditions. When ranking the results of these algorithms and comparing it to the ranking based on human perception, wEscore turned out to be more accurate than Escore.

Search for image quality metrics suitable for assessing images specially precompensated for users with refractive errors

“…Note that in our procedure we deliberately did not use Kendall or Spearman rank correlation, which is often employed to compare ranked lists [18,19]. This is because our procedure did not simply fix the same or opposite choice of the winner and the loser in the pair, but explicitly used the fact that in some pairs people were absolutely confident in the winner (and the metric that agreed with them received an increment of 1, and the one that disagreed received 0), and in some other pairs they gave a result close to a draw, and on such pairs no metrics could get a significant advantage over each other, which could happen when using the Kendall/Spearman rank correlation.…”