Fast Depth Intra Coding Based on Depth Edge Classification Network in 3D-HEVC
نویسندگان
چکیده
As the extension of high efficiency video coding (HEVC) standard, three dimensional-HEVC (3D-HEVC) is latest 3D standard. 3D-HEVC adopts many complicated algorithms to generate additional intermediate views for representation, which result in extremely complexity. Therefore, this paper proposed a fast depth intra approach reduce complexity, based on convolutional neural network (CNN). First, we established database independent view map, includes unit (CU) partition data map. Second, constructed edge classification CNN (DEC-CNN) framework classify edges map and embedded into test platform. Finally, utilized pixel value binarized image correct above results. The experimental results demonstrated that our can time by 72.5% average under negligible degradation performance. This outperforms other state-of-the-art methods complexity 3D-HEVC.
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ژورنال
عنوان ژورنال: IEEE Transactions on Broadcasting
سال: 2022
ISSN: ['0018-9316', '1557-9611']
DOI: https://doi.org/10.1109/tbc.2021.3106143