Implementing Bilinear Interpolation on Quantum Images

TL;DR

This paper introduces a quantum bilinear interpolation method for FRQI images, designing quantum circuits for image scaling and demonstrating improved image quality over traditional methods through simulations.

Contribution

It presents a novel quantum interpolation scheme with specific quantum modules and circuits, advancing quantum image processing techniques.

Findings

Quantum circuits for bilinear interpolation are successfully designed.

Simulation results show improved PSNR and SSIM over nearest neighbor interpolation.

The method effectively performs image up-scaling and down-scaling in quantum images.

Abstract

In this paper, we present an interpolation scheme for FRQI images based on bilinear interpolation. To accomplish this, we formulated several quantum modules, i.e., assignment module, increment module, and quarter module, and suffused them into our proposed quantum image interpolation circuit. The concrete quantum circuits to accomplish up-scaling and down-scaling based on bilinear for FRQI images are designed and the network complexities of them are analyzed. Finally, to validate the proposed method, simulation experiments to enlarge and reduce the test images are executed, whose results are compared with the nearest neighbor interpolation for FRQI images. The up-scaled images by using proposed interpolation algorithm achieve satisfactory results, and both PSNR and SSIM values are better than those of the nearest neighbor method.