Unifying Amplitude-Phase Coupling and Reliable Endogenous Priors for Low-Light Image Enhancement

Key points

• To address this issue, we propose a frequency-spatial framework that jointly models spectral interaction and reliable prior guidance.1
• We first empirically analyze the coupling between amplitude and phase and develop an Amplitude-Phase Adaptive Compensation Fusion (APACF) module.1
• Specifically, we treat an intermediate result, preliminarily restored in the frequency domain and already close to the ground-truth illumination, as a high-fidelity source for extracting complementary pseudo-infrared and gradient cues.1
• Based on ERP, we further design a Dual-Modal Guided Refinement Network (DGRN) to inject these purified structural cues into the decoder, thereby recovering missing fine textures more accurately.1

Sources (1)

• [1]Unifying Amplitude-Phase Coupling and Reliable Endogenous Priors for Low-Light Image Enhancement
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 17, 05:21 AM

  Frequency-domain methods have shown strong potential for low-light image enhancement (LLIE) because they can effectively regulate global illumination.

  To address this issue, we propose a frequency-spatial framework that jointly models spectral interaction and reliable prior guidance.

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