A Literature Survey on Image Fusion Methods for Remote Sensing Applications

The abundance of available image capturing technologies is driving up demand for fusing images in the domain of image processing. Image fusion creates a single composite image by merging pertinent input from several sensors using mathematical algorithms. This method preserves important aspects of the image while enhancing its quality by integrating complementary multi-sensor data into a one image. In applications including robot vision, satellite and aerial imaging, imaging for medical purposes, and robotic or vehicle guiding, it is a crucial pre-processing step. This research discusses the benefits and drawbacks of many state-of-the-art image fusion methodologies at different levels. Along with quality metrics, it also examines spatial and transform-based methodologies and their applicability across several fields. The paper concludes by outlining possible future developments for image fusion in diverse applications.