Abstract: Image fusion is a process of merging two or more images of same scene to generate single fused image which provide vital information in the fused image. Image fusion method is used for removing noise from the images. Noise is an unwanted material which decreases the quality of an image and affecting the clarity of fused image. Noise can be of different types such as impulse noise, Gaussian noise, uniform noise etc. Images distort some times during transmission or acquisition or due to fault memory locations in hardware. Image fusion can be occurring at three levels such as pixel level fusion, feature level and decision level fusion. A lot of research is being done in the field of multi focal image fusion and encompassing areas of Computer Vision, Image processing, parallel and distributed processing, Automatic object detection, Robotics and remote sensing. This paper is a detailed study performed over a sequence of image fusion methods and algorithms regarding their implementation. Research issues in Image Fusion techniques are to increase efficiency in term API, Standard deviation, PSNR, and try to generate more informative fused images.
Keywords: Image fusion, multi focal image, PSNR, Entropy.