Structure-Preserving Unpaired Image Translation to Photometrically Calibrate JunoCam with Hubble Data

2025-11-27

AI Summary

JunoCam lacks absolute photometric calibration, hindering quantitative analysis of Jupiter’s atmosphere. To address this, we propose SP-I2I—a structure-preserving unpaired image-to-image translation method—that introduces frequency-domain constraints into remote sensing image translation for the first time. By explicitly preserving high-frequency details, SP-I2I bridges the substantial resolution and spectral disparities between JunoCam and the Hubble Space Telescope (HST). Inspired by pansharpening, our approach jointly optimizes a structure-aware neural network architecture and a frequency-domain loss, enabling cross-sensor photometric alignment without pixel-level paired data. Experiments demonstrate that SP-I2I significantly outperforms existing state-of-the-art methods, markedly enhancing the quantifiability of fine-scale cloud structures on Jupiter and successfully supporting multi-source remote sensing data fusion tasks.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Computer Vision: Remote Sensing / Geospatial AI
• Machine Learning: Multimodal Learning

Application Category

• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs
• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data

Abstract

Insights into Jupiter's atmospheric dynamics are vital for understanding planetary meteorology and exoplanetary gas giant atmospheres. To study these dynamics, we require high-resolution, photometrically calibrated observations. Over the last 9 years, the Juno spacecraft's optical camera, JunoCam, has generated a unique dataset with high spatial resolution, wide coverage during perijove passes, and a long baseline. However, JunoCam lacks absolute photometric calibration, hindering quantitative analysis of the Jovian atmosphere. Using observations from the Hubble Space Telescope (HST) as a proxy for a calibrated sensor, we present a novel method for performing unpaired image-to-image translation (I2I) between JunoCam and HST, focusing on addressing the resolution discrepancy between the two sensors. Our structure-preserving I2I method, SP-I2I, incorporates explicit frequency-space constraints designed to preserve high-frequency features ensuring the retention of fine, small-scale spatial structures - essential for studying Jupiter's atmosphere. We demonstrate that state-of-the-art unpaired image-to-image translation methods are inadequate to address this problem, and, importantly, we show the broader impact of our proposed solution on relevant remote sensing data for the pansharpening task.

Problem

• Calibrate JunoCam photometrically using Hubble data
• Preserve high-frequency features in image translation
• Address resolution discrepancy between sensors

Innovation

• Unpaired image translation for photometric calibration
• Structure-preserving method with frequency-space constraints
• Addresses resolution discrepancy between JunoCam and Hubble