Vol. 1 No. 4 (2026)

Articles

Phase-Selective Spectral Routing for Real-Time Mobile Image Upscaling

Published 2026-08-12

  • Ayanda G. Mahlangu
    • ,
  • Daniel Naidoo

Ayanda G. Mahlangu
Department of Computer Science and Applied Mathematics, School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, Gauteng, South Africa

Daniel Naidoo
Department of Computer Science and Applied Mathematics, School of Computer Science and Applied Mathematics, University of the Witwatersrand, Johannesburg, Gauteng, South Africa

Data Science and Computational Intelligence, Volume 1, Issue 4, 2026 cover

Abstract

The demand for high-quality visual content on mobile devices has escalated rapidly, necessitating advanced image upscaling techniques that can operate within the stringent power and thermal constraints of mobile hardware. Traditional deep learning approaches to super-resolution often rely on computationally expensive spatial domain convolutions, rendering them unsuitable for real-time mobile applications such as video streaming and live gaming. This paper introduces a novel framework termed Phase-Selective Spectral Routing, which leverages frequency domain analysis to optimize the computational graph dynamically. By transforming input features into the spectral domain, the proposed architecture isolates critical high-frequency phase information essential for edge preservation and textural fidelity. A lightweight routing mechanism then selectively directs only the most salient spectral components through high-capacity neural pathways, while low-frequency amplitude information is processed via computationally inexpensive operations. This selective routing significantly reduces the number of floating-point operations required per pixel. Extensive experimental evaluations demonstrate that the proposed method achieves competitive structural similarity and peak signal-to-noise ratios compared to state-of-the-art spatial domain upscalers, while reducing inference latency by an order of magnitude on standard mobile systems-on-chip. The results indicate a promising direction for deploying sophisticated generative models on resource-constrained platforms without compromising visual integrity.

Keywords

Image Upscaling, Spectral Routing, Mobile Computing, Real-Time Processing

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