LCPNet: Latent Consistent Proximal Unfolding Network for Infrared Small Target Detection
LCPNet is a deep learning method for infrared small target detection that uses a latent space approach to unfold image decomposition. It solves problems by operating in this latent space, preserving physical constraints while avoiding repeated data compression between stages. The method introduces a Latent Consistent Proximal solver and Shared Optimization Memory to guide all decomposition variables coherently.