Neural Network-Based Reference Block Quality Enhancement for Motion Compensation Prediction

نویسندگان

چکیده

Inter prediction is a crucial part of hybrid video coding frameworks, and it used to eliminate redundancy in adjacent frames improve performance. During inter prediction, motion estimation find the reference block that most similar current block, following compensation shift fractionally obtain block. The closer original higher efficiency is. To quality blocks, enhancement network (RBENN) dedicated blocks proposed. main body consists 10 residual modules, with two convolution layers for preprocessing feature extraction. Each module convolutional layers, one ReLU activation, shortcut. uses luma as input before compensation, enhanced then filtered by default fractional interpolation. Moreover, proposed method can be both conventional affine compensation. Experimental results showed RBENN could achieve −1.35% BD rate on average under low-delay P (LDP) configuration compared latest H.266/VVC.

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ژورنال

عنوان ژورنال: Applied sciences

سال: 2023

ISSN: ['2076-3417']

DOI: https://doi.org/10.3390/app13052795