Résumé: Image fusion is a long-established and well-known study area of digital image processing. The reason is its substantial approach in several practical applications in which multi-focus image fusion (MFIF) is one of the most essential and commonly employed applications in the current situation. However, low contrast, colour distortion, and different fusion losses are significant challenges that must be addressed while generating the composite image. So, this study proposes an experimental and comprehensive review with an idea/methodology to encounter these challenges in which pre-hand enhancement criteria are applied for both gray-scale and colour images before fusion for multi-focus images. First, a detailed analysis of many categories and their sub-categories is offered, providing the groundwork for this study. Following this, we explain the enhancement methodology, which utilises the histogram for gray-scale and colour balancing for colour images. Besides this, several non-reference objective evaluation fusion metrics are also presented. In addition, simulation using MATLAB software from the conventional approach to the recent deep learning approach is carried out with and without enhancement for twenty state-of-the-art MFIF algorithms to check the validity of the adopted criteria. The results obtained with the enhancement approach as a pre-processing step show that almost all the outcomes are better or comparable with the original methodologies in both an objective and subjective manner. Moreover, the additional running time of just 0.2582 s at pre-processing stage indicates little computational complexity. Lastly, we discuss the current status of research, ongoing difficulties, and future possibilities.

Langue: Anglais