SkyRadar: A Cross-Platform Grayscale Radar Meteorology and Astrograph Analysis Engine for Atmospheric and Astronomical Imaging

Abstract

SkyRadar is a cross-platform grayscale radar and astrograph image analysis application designed for both mobile (iOS, Android) and desktop (macOS, Windows) environments. Unlike conventional RGB-based astrophotography tools, SkyRadar implements a grayscale-first analytical framework based on luminance modelling, enabling unified interpretation of atmospheric radar imagery and astronomical observations. The system integrates pixel-level processing techniques including RGB-to-grayscale conversion, brightness beam compensation, optical depth estimation, reflectivity normalization, and texture-based morphology analysis to extract physically meaningful information from two-dimensional imaging data. To evaluate the reliability of the grayscale standardisation methodology, a dataset of 200 imaging samples across 16 colour standards was analysed. Statistical analysis was conducted using Microsoft Excel (Microsoft Corporation, Redmond, Washington, USA). RGB values were converted into grayscale intensities (0–255) using the standard luminance equation (Gray = 0.299R + 0.587G + 0.114B). For a single Red–Violet standard imaged under varying conditions, the standardised grayscale dataset exhibited a standard deviation of 3.12, compared to 33.68 for non-standardised data, demonstrating a substantial improvement in measurement reproducibility. Across all 16 colour standards, the mean standard deviation decreased from 37.94 to 4.57, while the mean error percentage declined from 65.82% to 48.21% following standardisation. Post-hoc power analysis (α = 0.05) indicated statistical power exceeding 99% (β ≈ 0.01), confirming the robustness of the dataset. Beyond statistical validation, SkyRadar extends grayscale analysis to meteorological and astrophysical applications, including cloud density estimation, cyclone morphology classification, radar attenuation modelling, surface brightness profiling, and celestial signal decomposition. The results demonstrate that grayscale-first processing provides a stable and physically interpretable framework for analysing both atmospheric and astronomical imaging data. By integrating radar physics with astrophotometric principles in a unified platform, SkyRadar enables reproducible, cross-domain image analysis suitable for professional researchers, meteorologists, and amateur observers.