Table 1. Visual features that can be described as linear combinations in the log stimulus space.

These feature abbreviations are used throughout the text. Formulae show relationship between each feature and the number, size, and spacing variables used in the regression model.

Visual Feature	Abbr.	Equation in terms of log of number, size and spacing
Number	Num	log (Num)
Size	Sz	log (Sz)
Total Area	TA	$\log (TA)=\frac{1}{2}\log (Num)+\frac{1}{2}\log (Sz)$
Item Area	IA	$\log (IA)=-\frac{1}{2}\log (Num)+\frac{1}{2}\log (Sz)$
Spacing	Sp	log(Sp)
Field Area	FA	$\log (FA)=\frac{1}{2}\log (Num)+\frac{1}{2}\log (Sp)$
Sparsity	Spar	$\log (Spar)=-\frac{1}{2}\log (Num)+\frac{1}{2}\log (Sz)$
Scale	Sc	$\log (Sc)=\frac{1}{2}\log (Sz)+\frac{1}{2}\log (Sp)$
Coverage	Cov	$\log (Cov)=-\frac{1}{2}\log (Sp)+\frac{1}{2}\log (Sz)$