A GRADIENT-BASED HYBRID IMAGE FUSION SCHEME USING OBJECT EXTRACTION

This paper presents a new hybrid image fusion scheme that combines features of pixel and region based fusion, to be integrated in a surveillance system. In such systems, objects can be extracted from the different set of images due to background availability, and transferred to the new composite image with no additional processing usually imposed by other fusion approaches. The background information is then fused in a multi-resolution pixel-based fashion using gradient-based rules to yield a more reliable feature selection. According to Piella and Petrovic quantitative evaluation metrics, the proposed scheme exhibits a superior performance compared to existing fusion algorithms.