To mitigate color crosstalk in projected images induced by non-uniform projection surfaces and dynamic ambient lighting, we propose MAPCNet, an adaptive photometric compensation network that enables robust color reproduction across diverse environments. The experimental process begins with a mask-based preprocessing operation on a multi-surface photometric compensation dataset captured under varying ambient light conditions. The algorithm incorporates a multi-attention mechanism and a triple-interaction attention mechanism, and further integrates a hybrid attention module inspired by the Transformer architecture. By integrating channel attention and window-based self-attention, this module improves the network’s adaptability to spatial and illumination changes. Experimental results demonstrate that the photometric compensation achieved by this algorithm meets the visual perception requirements of the human eye.
Zhang et al. (Tue,) studied this question.