IMR Analysis — Lunar Surface Structural Field

This study presents a computational structural analysis of a high-resolution lunar surface image using the IMR (Informational Morphological Reconstruction) framework. The analysis combines multiple deterministic image descriptors including luminance normalization, local entropy mapping, gradient magnitude, edge density and symmetry estimation. These descriptors are integrated into an aggregated informational field reconstruction describing spatial organization within the lunar terrain. A distributed Region-of-Interest (ROI) statistical analysis is performed using histogram-preserving surrogate models in order to test whether local spatial organization differs from randomized luminance arrangements. The study also introduces a Morphological Transformation (MT) sequence that provides a multi-stage visualization of structural organization across the image, followed by field-based renderings including saliency maps, edge structure analysis, R-index proxy mapping and Unified Informational Field (UIF) visualization. The results illustrate how deterministic computational transformations can reveal spatial organization embedded in planetary surface imagery without introducing synthetic structures. This case study demonstrates the potential of the IMR framework for scientific imaging analysis in planetary science, remote sensing and computational morphology.