Image fusion using statistical intensity fusion and adaptive unsharp masking

Image fusion is an image processing technique that is applied in various application areas. Image fusion is adopted for target detection and recognition in surveillance systems, recognition and diagnosis for medical imaging systems and for surface characteristics determination on multi-spectral satellite images. Structure of the techniques and the content of the resulting images vary with respect to the application area. In this work, an image fusion technique that can run at real-time environment to be applied in surveillance systems is proposed. Technique enables the integration of scene components without suppression, especially for operators to observe all scene components on a single image. Technique is compared with other techniques existent in the literature using quantitative tests and observed that it provides better results in the scene components and their details and total quality metrics.