Image Quality Assessment Using Self-Adaptable Bacterial Foraging Optimization Algorithm a Review
نویسندگان
چکیده
here are number of successful image quality metrics that rely on the structural information in an image in order to assess its perceptual quality. It is a challenging task to extract the structural information that is perceptually meaningful to the visual system. The current research is motivated by the observation that there is no single metric that provides the best performance scores in all conditions. This paper presents a new approach for objective image quality assessment using self-adaptable bacterial foraging optimization algorithm (SABFOA). Moreover, multi-metric fusion approach is used for objective image quality assessment. BFOA is inspired from the social foraging behaviour of bacteria “Escherichia Coli”. BFOA, because of its efficiency to solve the realworld optimization problems, has drawn the attention of several researchers. The underlying biology behind the foraging strategy of E.coli has been emulated in an extraordinary manner and is used as a simple optimization
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