Novel Quality Measures for Image Fusion Based on Structural Similarity and Visual Attention Mechanism
| Autor: | Xianyi Ren, Xiujian Liu, Tao Hu, Jihong Zhang |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Measure (data warehouse)
Image fusion genetic structures business.industry Structural similarity media_common.quotation_subject ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Visualization Image (mathematics) Correlation Salient Quality (business) Computer vision Artificial intelligence business Mathematics media_common |
| Zdroj: | 2010 International Conference on Multimedia Technology. |
| DOI: | 10.1109/icmult.2010.5630969 |
| Popis: | A novel objective quality for image fusion based on structural similarity and visual attention mechanism (VAM) is presented. By giving higher weight to the salient areas in the input images, the quality measure can estimate how much visual meaningful information is preserved in the fused image. The correlation analysis between objective measure and subjective evaluation showed that our measures are more consistent with human subjective evaluation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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