Design of correlation filters for recognition of linearly distorted objects in linearly degraded scenes.
Generalized correlation filters are proposed to improve recognition of a linearly distorted object embedded in a nonoverlapping background when the input scene is degraded with a linear system and additive noise. Several performance criteria defined for the nonoverlapping signal model are used for the design of filters. The derived filters take into account information about an object to be recognized, disjoint background, noise, and linear degradations of the target and the input scene. Computer simulation results obtained with the proposed filters are discussed and compared with those of various correlation filters in terms of discrimination capability, location errors, and tolerance to input noise.
Ramos-Michel
Erika M
EM
Department of Computer Science, Centro de Investigación Científica y de Educacíon Superior de Ensenada, Km. 107 Carretera Tijuana-Ensenada, Ensenada 22860, BC, Mexico.
Kober
Vitaly
V