Abstract

Despite the recent plethora of empirical attempt at improving image quality in the emerging image processing field, image resolution is pressingly fraught with dire challenges today. Image enhancement research remained progressive because of the advancement in contemporary globalization that mandates an improvement in image quality and it becomes essential to run the best quality of image in some applications such as in forensic unit where in order to obtain the best information, image has to be enlarged in terms of size. Degraded image, often occasioned by motion blur, inaccurate focusing and sensor noise aggregate during the process of acquiring image through an image acquisition device (Camera). The improvisational capacity of super resolution imaging algorithm compensates this degradations by reconstructing a high resolution image from honing and harnessing single or multiple low resolution image to facilitate and foster enhanced visual contents and scene recognitions. High quality images are required in applications of different fields, such as remote sensing, satellite imaging, surveillance, medical imaging, etc. This paper attempts a conceptual enquiry and presents an overview of the conventional techniques of super resolution, how the techniques works along with their pros and cons accordingly, recent improvements carried out by different researchers are dutifully delineated. The Iterative back projection (IBP) method is hereby suggested a promising super resolution method due to its unique features highlighted.

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