IEEE Trans Image Process - Diffuse prior monotonic likelihood ratio test for evaluation of fused image quality measures.

Tópicos

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Resumo

This paper introduces a novel method to score how well proposed fused image quality measures (FIQMs) indicate the effectiveness of humans to detect targets in fused imagery. The human detection performance is measured via human perception experiments. A good FIQM should relate to perception results in a monotonic fashion. The method computes a new diffuse prior monotonic likelihood ratio (DPMLR) to facilitate the comparison of the H(1) hypothesis that the intrinsic human detection performance is related to the FIQM via a monotonic function against the null hypothesis that the detection and image quality relationship is random. The paper discusses many interesting properties of the DPMLR and demonstrates the effectiveness of the DPMLR test via Monte Carlo simulations. Finally, the DPMLR is used to score FIQMs with test cases considering over 35 scenes and various image fusion algorithms.

Resumo Limpo

paper introduc novel method score well propos fuse imag qualiti measur fiqm indic effect human detect target fuse imageri human detect perform measur via human percept experi good fiqm relat percept result monoton fashion method comput new diffus prior monoton likelihood ratio dpmlr facilit comparison h hypothesi intrins human detect perform relat fiqm via monoton function null hypothesi detect imag qualiti relationship random paper discuss mani interest properti dpmlr demonstr effect dpmlr test via mont carlo simul final dpmlr use score fiqm test case consid scene various imag fusion algorithm

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