Stochastic Rounding for Image Interpolation and Scan Conversion

TL;DR

This paper introduces a stochastic rounding method for image interpolation and scan conversion, demonstrating its effects and advantages over traditional deterministic rounding through simulations and ultrasound video applications.

Contribution

It proposes a novel stochastic rounding function based on pseudorandom numbers for improved image interpolation and scan conversion, especially in ultrasound imaging.

Findings

Stochastic rounding improves image quality in interpolation.

NNI-SR outperforms traditional NNI-DR in certain scenarios.

Enhanced performance in ultrasound scan conversion.

Abstract

The stochastic rounding (SR) function is proposed to evaluate and demonstrate the effects of stochastically rounding row and column subscripts in image interpolation and scan conversion. The proposed SR function is based on a pseudorandom number, enabling the pseudorandom rounding up or down any non-integer row and column subscripts. Also, the SR function exceptionally enables rounding up any possible cases of subscript inputs that are inferior to a pseudorandom number. The algorithm of interest is the nearest-neighbor interpolation (NNI) which is traditionally based on the deterministic rounding (DR) function. Experimental simulation results are provided to demonstrate the performance of NNI-SR and NNI-DR algorithms before and after applying smoothing and sharpening filters of interest. Additional results are also provided to demonstrate the performance of NNI-SR and NNI-DR interpolated scan conversion algorithms in cardiac ultrasound videos.