Discrete Curvelet Transform Based Super-resolution using Sub-pixel Image Registration
Anil A. Patil, Jyoti Singhai · International Journal of Signal Processing Image Processing and Pattern Recognition · 2011
All the time, there is a demand of High-Resolution (HR) images in electronic imaging applications. Super-Resolution (SR) is an approach used to restore High-Resolution (HR) image from one or more Low-Resolution (LR) images. The goal of SR is to extract the independent information from each LR image in that set and combine the information into a single high resolution (HR) image. The quality of reconstructed SR image obtained from a set of LR images depends upon the registration accuracy of LR images. In this paper SR reconstruction using a sub-pixel shift image registration and Fast Discrete Curvelet transform (FDCT) for image interpolation is proposed. The Curvelet transform is a multiscale pyramid with many directions and positions at each scale. Image interpolation is performed at the finest level in Curvelet domain. Experimentation based results have shown appropriate improvements in PSNR and MSE. Also, it is experimentally verified that the computational complexity of the SR algorithm is reduced.