# Evaluation of Rounding Functions in Nearest-Neighbor Interpolation

arXiv: https://arxiv.org/abs/2003.06885 · HTML: https://mlsanity.com/paper/2003.06885/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Mar 2020.

## Built on by (most cited first, 8 of 8)

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- [Stochastic Rounding for Image Interpolation and Scan Conversion](https://mlsanity.com/paper/2110.12983/) (2021)
- [Beyond Nearest Neighbor Interpolation in Data Augmentation](https://mlsanity.com/paper/2504.01527/) (2025)
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## Abstract (arXiv)

A novel evaluation study of the most appropriate round function for nearest-neighbor (NN) image interpolation is presented. Evaluated rounding functions are selected among the five rounding rules defined by the Institute of Electrical and Electronics Engineers (IEEE) 754-2008 standard. Both full- and no-reference image quality assessment (IQA) metrics are used to study and evaluate the influence of rounding functions on NN interpolation image quality. The concept of achieved occurrences over targeted occurrences is used to determine the percentage of achieved occurrences based on the number of test images used. Inferential statistical analysis is applied to deduce from a small number of images and draw a conclusion of the behavior of each rounding function on a bigger number of images. Under the normal distribution and at the level of confidence equals to 95%, the maximum and minimum achievable occurrences by each evaluated rounding function are both provided based on the inferential analysis-based experiments.