A Quality Metric Based on Color Similarity for Image Fusion

This paper proposes a new objective, non-reference quality metric for evaluating the performance of pixel-level image fusion. The metric is designed on a likelihood function for color cue that measures the similarity of color- or grey-level distributions. We have provided a theoretical analysis on how the quality metric responds to weighted averaging fusion algorithm. Then the slide window is used to calculate the metric over local region with the weight which is assessed by local saliency and indicates the relative importance. Extensive experiments have demonstrated that the metric is more effective and consistent with subjective evaluations compared with other metrics.

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