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After applying the psychometric function, we combine each band using the probability summation formula (Eq. 18) [2].
Using the probability summation model as discussed previously, the noisiness measure D for the whole image I is obtained by using a Minkowski metric for inter-block pooling as follows: D = ∑ R b D R b α 1 / α (17).
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This work firstly presents a full-reference noisiness metric based on the probability summation model presented in the previous sections.
In the previous section, a full-reference quality metric is presented based on the probability summation model and JND.
The accuracy results were modeled using a probability summation model which demonstrated that accuracy on full images was greater than that expected from performance on the two individual halves.
The algorithm is defined using the linear summation of input patterns and their randomized input weights.
Using the Gauss summation theorem (4.7), the result follows easily.
We estimated total serum lipids (TL) using the enzymatic summation method (Akins et al. 1989).
Total lipid concentrations were estimated using the enzymatic summation method (Akins et al. 1989).
As before, M g (A i ) can be calculated efficiently using the Subset Summation Tree.
Total lipids were calculated using the summation method reported by Phillips et al. (1989).
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