Learning Spatiotemporal Features for Single Image Stripe Noise Removal

Learning Spatiotemporal Features for Single Image Stripe Noise Removal

Blog Article

The stripe noise caused by nonuniform response of different detectors Default limits the sensitivity of the infrared imaging system and reduces the image quality.Existing destriping methods still struggle to remove the stripe noise as well as recover the image details, which restricts the application of the infrared focal plane array (IRFPA) imager.In this paper, an innovative destriping method through the perspective of spatiotemporal feature modeling is proposed, which excavates the intrinsic spatial characteristics of stripe noise as well as the redundant temporal information between the adjacent ELDER FLOWERS frames to estimate the stripe component more precisely.Moreover, the bidirectional fusion strategy that further strengthens the long-time correlation is introduced to separate the scene details from stripe noise more thoroughly.Experimental results show that the proposed model outperforms existing classical destriping methods on both simulated images and real data.