Survey on Image Fusion Techniques

The advantages of image fusion include image sharpening, feature enhancement, improved classification, and creation of stereo data sets. Multisensor image fusion provides the benefits in terms of range of operation, spatial and temporal characteristics, system performance, reduced ambiguity and improved reliability. Based on the processing levels, image fusion techniques can be divided into different categories. These are pixel level, feature level and symbol level/decision level. Pixel level method is the simplest and widely used method. This method processes pixels in the source image and retains most of the original image information. Compared to other two methods pixel level image fusion gives more accurate results. Feature level method processes the characteristics of the source image. This method can be used with the decision level method to fuse images effectively. Because of the reduced data size, it is easier to compress and transmit the data. The top level of image fusion is decision making level. It uses the data information extracted from the pixel level fusion or the feature level fusion to make optimal decision to achieve a specific objective. Moreover, it reduces the redundancy and uncertain information Citation: Nav Jyoti Prakash Pandey, Mr. Apoorv Mishra. "Survey on Image Fusion Techniques." Global Research and Development Journal For Engineering 4.9 (2019): 1 - 4.