Quadratic filter and feature detection
Kae-Jy Chou, Brian G. Schunck · 2002
The quadratic filter for low-level vision applications is explored. The quadratic filter is the simplest nonlinear time-invariant filter and corresponds to the second term in the Volterra expansion. Concepts behind the quadratic filter are elaborated, and it is shown that it can be derived from fundamental properties of regions and the principle of model competition. Two properties of the filter are presented. It has better spatial localization than a linear filter, and it is insensitive to blurred boundaries.>