In this correspondence, we propose a novel image resolution enhancement algorithm based on discretewavelet transform (DWT), stationary wavelet transform (SWT) and sparse signal recovery of the inputimage. The nonlocal means filter is employed in the preliminary denoising stage of the proposed method.The denoised input low resolution (LR) image is then decomposed into different frequency subbands byemploying DWT and SWT simultaneously. In parallel, the denoised LR image is subjected to a sparse signalrepresentation based interpolation. All the estimated high frequency subbands as well as the sparseinterpolated LR image are fused to generate a high resolution (HR) image by using inverse discrete wavelettransform (IDWT). Experimental results on various test images show the superiority of our method over theconventional and state-of-the-art single image super- resolution (SR) techniques in achieving the real timeperformance.
Improved Super-Resolution Ultrasound Microvessel Imaging With Spatiotemporal Nonlocal Means Filtering and Bipartite Graph-Based Microbubble Tracking
