Spatial super resolution based image reconstruction using HIBP

Spatial image resolution explains about the pixel density in a digital image. As a result more the number of pixels more detailed visibility of information contained in the image. Hardware limitations restrict the increase in number of sensor elements per unit area in camera. Therefore an imaging system with inadequate sensor array will generate low resolution image which causes pixelization effect in them. This problem is solved in software level using signal processing techniques called super resolution based image reconstruction. In this paper super resolution based image reconstruction problem is addressed, which is used for resolution enhancement. Unlike interpolation, it takes information from multiple number of low resolution images with sub-pixel shifts and contain nonredundant data to generate a high resolution image. In this proposed reconstruction method, a hybrid iterative back projection technique is developed exploiting the notion of cuckoo search optimization algorithm in iterative back projection method. The high resolution solution from iterative back projection method is optimized using Cuckoo optimization algorithm. The performance of the proposed algorithm is found to be outperforming that of existing IBP and other interpolation based reconstruction techniques.