Multi-scale HSV Color Feature Embedding for High-fidelity NIR-to-RGB Spectrum Translation

Understand

The NIR-to-RGB spectral domain translation is a formidable task due to the inherent spectral mapping ambiguities within NIR inputs and RGB outputs.

• Thus, existing methods fail to reconcile the tension between maintaining texture detail fidelity and achieving diverse color variations.
• In this paper, we propose a Multi-scale HSV Color Feature Embedding Network (MCFNet) that decomposes the mapping process into three sub-tasks, including NIR texture maintenance, coarse geometry reconstruction, and RGB color prediction.
• Thus, we propose three key modules for each corresponding sub-task: the Texture Preserving Block (TPB), the HSV Color Feature Embedding Module (HSV-CFEM), and the Geometry Reconstruction Module (GRM).