image processing, fusion, sharpness, blur, F-Transform

During our research, we have presented a novel approach for multi-focus image fusion based on new image sharpness measures built on F-Transform. We have already presented that F-Transform based sharpness measure subjectively give good results in edge detection and sharpness evaluation. In order to continue with our research, we need to prove that such F-Transform based measures are generally usable as sharpness measures in image processing. So we aimed at our measures trying to evaluate their stability and robustness against noise. In the contribution, we present theoretical background and properties requested to be satisfied by sound sharpness measures. Then, we presented one previously introduced and one novel F-Transform based sharpness measure, and according to the presented properties, we verified that the proposed measures are fulfilling stated properties. The verification is done over experimental and real-life images and is evaluated referring to the standard simple sharpness measures. The result is that both F-Transform based proposed measures supports presented properties and can be generally used as image sharpness measures.