Transformer-based despeckling for laser active polarimetric imaging.

Laser active polarization imaging is susceptible to coherent speckle noise, which severely degrades both image quality and the accuracy of polarization parameter estimation. Existing polarimetric denoising methods, predominantly designed for additive noise models, struggle to handle speckle noise due to its complex statistical characteristics while failing to fully exploit the structural correlations among multi-channel polarization images. To address these limitations, this study proposes a polarimetric speckle suppression network named PoDeFormer, which achieves effective speckle removal by establishing the intrinsic connection between incoherent illumination and coherent speckle in laser active polarization imaging. Experimental results demonstrate that the network not only effectively removes speckle noise while preserving polarization information integrity but also enables fast inference with minimal computational overhead, providing an efficient and reliable solution for real-time denoising in laser active polarization imaging applications.