IEEE Transactions on Broadcasting · 2021 · 69 citations · 39 references
ComputingComputer ScienceComputer GraphicsComputer VisionData StructuresCoding TheoryData CompressionDecision TreesImage CompressionRate-distortion TheorySource CodingCodingComplexityDecision Model OptimizationEncoder DesignImage EncodingPipeline OrganizationRate-distortion OptimizationVideo Compression
Versatile video coding (VVC) further improves video coding gain by introducing a new Quad-tree (QT) with nested multi-type tree (QTMT) partition structure, which includes QT partition, horizontal and vertical binary-tree (BT) partition, and horizontal and vertical ternary-tree (TT) partition. However, the coding gain is achieved at the cost of drastically increased coding complexity. We propose an early intra coding unit (CU) size partition method for VVC based on a tunable decision model. The distortion of the CU is firstly obtained by the difference between the original luminance pixel and the predicted one. By exploiting the distortion, two decision models are established for the early skipping of BT and TT partition for each CU, respectively. Then, a tunable decision model is presented to achieve different trade-off between encoding loss and complexity reduction. Extensive experimental results show that the proposed approach reduces the encoding time ranging from 22.6% to 67.6% with the BD-Rate increase ranging from 0.56% to 2.61%. It is also suitable for parallel implementation by exploiting the pipeline structure of the VVC encoder due to its independency with neighboring CU blocks.
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Reducing Complexity of HEVC: A Deep Learning Approach
Mai Xu, Tianyi Li, Zulin Wang et al. · IEEE Transactions on Image Processing · 2018 · 324 citations · Full text