Attention-based neural network for polarimetric image denoising
Hedong Liu, Yizhu Zhang, Zhenzhou Cheng, Jingsheng Zhai, Haofeng Hu
Abstract
In this Letter, we propose an attention-based neural network specially designed for the challenging task of polarimetric image denoising. In particular, the channel attention mechanism is used to effectively extract the features underlying the polarimetric images by rescaling the contributions of channels in the network. In addition, we also design the adaptive polarization loss to make the network focus on the polarization information. Experiments show that our method can well restore the details flooded by serious noise and outperforms previous methods. Moreover, the underlying mechanism of channel attention is revealed visually.
Topics & Concepts
Computer sciencePolarimetryArtificial neural networkNoise reductionArtificial intelligenceFocus (optics)Polarization (electrochemistry)Channel (broadcasting)Computer visionOpticsTelecommunicationsScatteringPhysicsChemistryPhysical chemistryImage and Signal Denoising MethodsOptical Polarization and EllipsometryAdvanced Image Fusion Techniques