EDIZ: An Error Diffusion Image Zooming Scheme

TL;DR

This paper introduces EDIZ, a new image zooming algorithm that enhances detail creation and reduces blurring through a zoom-out-zoom-in strategy, resulting in visually improved images.

Contribution

The paper presents a novel zooming scheme that improves detail synthesis and image quality using an error diffusion approach with a zoom-out-zoom-in process.

Findings

Enhanced image detail creation

Reduced blurring effects

Visually pleasing zoomed images

Abstract

Interpolation based image zooming methods provide a high execution speed and low computational complexity. However, the quality of the zoomed images is unsatisfactory in many cases. The main challenge of super- resolution methods is to create new details to the image. This paper proposes a new algorithm to create new details using a zoom-out-zoom-in strategy. This strategy permits reducing blurring effects by adding the estimated error to the final image. Experimental results for natural images confirm the algorithm's ability to create visually pleasing results.