Performance Comparision of Different Image Fusion Techniques for Multi-Focus and Multi-Modal Images
Abstract: Image fusion is the process of combining information from two or more images of a scene into a single composite image that is more informative and is more suitable for visual perception or computer processing. The objective in image fusion is to reduce uncertainty and minimize redundancy in the output while maximizing relevant information particular to an application or task. Given the same set of input images, different fused images may be created depending on the specific application and what is considered relevant information. In this paper, we compare different image fusion techniques such as DWT, DTCWT and Curvelet Transform by using different types of filters and decomposition levels for multi-focus images and multi-modal images.
Keywords: Image fusion, Curvelet Transform, multi-focus, multi-modal
How to Cite?: Dr. S. Narayana Reddy, Y. Sree Vaishnavi, "Performance Comparision of Different Image Fusion Techniques for Multi-Focus and Multi-Modal Images", Volume 5 Issue 12, December 2016, International Journal of Science and Research (IJSR), Pages: 1989-1994, https://www.ijsr.net/getabstract.php?paperid=ART20163943, DOI: https://dx.doi.org/10.21275/ART20163943