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Deep Multi-Scale Convolutional Neural Network for …
Deep Multi-Scale Convolutional Neural Network for Dynamic Scene DeblurringSeungjun NahTae Hyun KimKyoung Mu LeeDepartment of ECE, ASRI, Seoul National University, 151-742, Seoul, Korea{ , blind deblurring for general dynamicscenes is a challenging computer vision problem as blursarise not only from multiple object motions but also fromcamera shake, scene depth variation. To remove thesecomplicated motion blurs, conventional energy optimiza-tion based methods rely on simple assumptions such thatblur kernel is partially uniform or locally linear. More-over, recent machine learning based methods also dependon synthetic blur datasets generated under these assump-tions. This makes conventional deblurring methods fail toremove blurs where blur kernel is dif cult to approximate orparameterize ( object motion boundaries).}
motion only. However, in dynamic scenes, the kernel es-timation is more challenging as there are multiple moving objects as well as camera motion. Thus, Kim et al. [14] pro-posed a dynamic scene deblurring method that jointly seg-ments and deblurs a non-uniformly blurred image, allowing the estimation of complex (non-linear) kernel within a seg ...
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