Shock filter based image super-resolution using dual-tree complex wavelet transform and singular value decomposition

Purpose – The purpose of this paper is to present an improved wavelet-based approach in single image super resolution (SISR). The proposed method generates high resolution (HR) images by preserving the image contrast and edges simultaneously. Design/methodology/approach – Covariance-based interpolation algorithm is employed to obtain an initial estimate of the unknown HR image. The proposed method preserves the image contrast, by applying singular value decomposition (SVD)-based correction on the dual-tree complex wavelet transform coefficients. In addition, the dual operating mode diffusion based shock filter (DBSF) ensures noise mitigation and edge preservation. Findings – Experimental results on various test images reveal superiority of the proposed method over the existing SISR techniques in terms of peak signal to noise ratio, structural similarity index measure and visual quality. Originality/value – With SVD-based correction, the proposed method preserves the image contrast and also the DBSF operation helps to achieve sharper edges.