LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

A Total Fractional-Order Variation Model for Image Super-Resolution and Its SAV Algorithm

Photo by usgs from unsplash

Single-image super-resolution reconstruction aims to obtain a high-resolution image from a low-resolution image. Since the super-resolution problem is ill-posed, it is common to use a regularization technique. However, the choice… Click to show full abstract

Single-image super-resolution reconstruction aims to obtain a high-resolution image from a low-resolution image. Since the super-resolution problem is ill-posed, it is common to use a regularization technique. However, the choice of the fidelity and regularization terms is not obvious, and it plays a major role in the quality of the desired high resolution image. In this paper, a hybrid single-image super-resolution model integrated with total variation (TV) and fractional-order TV is proposed to provide an effective reconstruction of the HR image. We develop an efficient numerical scheme for this model using the scalar auxiliary variable approach with an adaptive time stepping strategy. Thorough experimental results suggest that the proposed model and numerical scheme can reconstruct high quality results both quantitatively and perceptually.

Keywords: resolution; image; fractional order; super resolution; model; image super

Journal Title: Journal of Scientific Computing
Year Published: 2020

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.