Abstract:
With the advancement field of imaging and multimedia tools and applications, photosensitive information presented by images is the foremost source of knowledge acquirement. In the practice of photosensitive information acquirement, storage, handling and transmission, some antiquity and noise can be acquainted with images that can damage photosensitive quality of the images. Usually, in digital imaging system, images are captured and converted into digital signal with the help of different sensors. This unprocessed signal of digital image signal is then handled to reduce noise and then compressed for the storage or transmission. When the end user finally observes the image, it can be different from the original form due to its exposure to innumerable varieties of distortions. Image fusion is an advantageous job in image and video enrichment practices. It is very necessary to state the proper standard for the quality assessment of fused images on the origin of subjective analysis. Existing models and techniques for image quality assessment are not very competent for all sorts of images and operational conditions specifically for images of moving entities, remote sensing constraints and medical applications. The research aims to propose image quality assessment technique with the objectives to assess the quality of images with subjective data analysis along with the inclusion of contrast, structural similarity and luminance and to improve the quality measure for images of all environments and exposures. Image fusion is grouping of more than two or two images acquired with different sensors or functioning conditions to craft the efficient outcome in one image. This work focuses on a novel quality assessment technique for multi -exposure fused images in image fusion specifically and in general
