IceNet for Interactive Contrast Enhancement
نویسندگان
چکیده
A CNN-based interactive contrast enhancement algorithm, called IceNet, is proposed in this paper, which enables a user to adjust image easily according his or her preference. Specifically, provides parameter for controlling the global brightness and two types of scribbles darken brighten local regions an image. Then, given these annotations, IceNet estimates gamma map pixel-wise correction. Finally, through color restoration, enhanced obtained. The may provide annotations iteratively obtain satisfactory also capable producing personalized automatically, can serve as basis further adjustment if so desired. Moreover, train effectively reliably, we propose three differentiable losses. Extensive experiments demonstrate that users with satisfactorily images.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2021
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2021.3137993