VIDEO COMPRESSION USING NESTED QUADTREE STRUCTURES, LEAF MERGING, AND IMPROVED TECHNIQUES FOR MOTION REPRESENTATION AND ENTROPY CODING Present by fakewen.

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Presentation transcript:

VIDEO COMPRESSION USING NESTED QUADTREE STRUCTURES, LEAF MERGING, AND IMPROVED TECHNIQUES FOR MOTION REPRESENTATION AND ENTROPY CODING Present by fakewen

introduction

Video Compression Using Nested Quadtree Structures  A video coding architecture is described that is based on nested and pre-configurable quadtree structures for flexible and signal-adaptive picture partitioning.  partitioning concept is to provide a high degree of adaptability for both temporal and spatial prediction

Leaf merging  leaf merging mechanism is included in order to prevent excessive partitioning of a picture into prediction blocks and to reduce the amount of bits for signaling the prediction signal.

Improved Techniques for Motion Representation  For fractional-sample motion-compensated prediction, a fixed-point implementation of the maximal-order-minimum-support algorithm is presented that uses a combination of infinite impulse response and FIR filtering.

Entropy Coding  Entropy coding utilizes the concept of probability interval partitioning entropy codes that offers new ways for parallelization and enhanced throughput.

outline  Overview of the Video Coding Scheme  Picture Partitioning for Prediction and Residual Coding  Motion-Compensated Prediction  Spatial Intra Prediction  Variable Block-Size Spatial Transforms and Quantization  Internal Bit Depth Increase  In-Loop Filtering  Entropy Coding  Encoder Control  Coding Conditions and Results

outline  Overview of the Video Coding Scheme  Picture Partitioning for Prediction and Residual Coding  Motion-Compensated Prediction  Spatial Intra Prediction  Variable Block-Size Spatial Transforms and Quantization  Internal Bit Depth Increase  In-Loop Filtering  Entropy Coding  Encoder Control  Coding Conditions and Results

Overview of the Video Coding Scheme  Wide-range variable block-size prediction  Nested wide-range variable block-size residual coding  Merging of prediction blocks  Fractional-sample MOMS interpolation  Adaptive in-loop filter  PIPE coding

Wide-range variable block-size prediction  the size of prediction blocks can be adaptively chosen by using a quadtree-based partitioning.  Maximum (Nmax ) and minimum (Nmin ) admissible block edge length can be specified as a side information. Nmax = 64 and Nmin = 4.

Nested wide-range variable block- size residual coding  the block size used for discrete cosine transform (DCT)-based residual coding is adapted to the characteristics of the residual signal by using a nested quadtree-based partitioning of the corresponding prediction block.

Merging of prediction blocks  in order to reduce the side information required for signaling the prediction parameters, neighboring blocks can be merged into one region that is assigned only a single set of prediction parameters.

Fractional-sample MOMS interpolation  Interpolation of fractional-sample positions for motion-compensated prediction is based on a fixed-point implementation of the maximal-order- minimum-support (MOMS) algorithm using an infinite impulse response (IIR)/FIR filter

Adaptive in-loop filter  in addition to the deblocking filter, a separable 2-D Wiener filter is applied within the coding loop. The filter is adaptively applied to selected regions indicated by the use of quadtree- based partitioning

PIPE coding  the novel probability interval partitioning entropy (PIPE) coding scheme provides the coding efficiency and probability modeling capability of arithmetic coding at the complexity level of Huffman coding.

outline  Overview of the Video Coding Scheme  Picture Partitioning for Prediction and Residual Coding  Motion-Compensated Prediction  Spatial Intra Prediction  Variable Block-Size Spatial Transforms and Quantization  Internal Bit Depth Increase  In-Loop Filtering  Entropy Coding  Encoder Control  Coding Conditions and Results

Picture Partitioning for Prediction and Residual Coding  The concept of a macroblock as the basic processing unit in standardized video coding is generalized to what we call a coding tree block (CTB).

 Dividing each picture into CTBs and further recursively subdividing each CTB into square blocks of variable size allows to partition a given picture of a video signal in such a way that both the block sizes and the block coding parameters such as prediction or residual coding modes will be adapted to the specific characteristics of the signal at hand.

 Fig. 1 illustrates  an example, where transform blocks and their corresponding  RQTs are shown in dashed lines. Note that the transform  block size that corresponds to the root node of a given RQT  is identical to the size of the related prediction block, or  equivalently, the leaf of the prediction quadtree, to which the  RQT is associated.

outline  Overview of the Video Coding Scheme  Picture Partitioning for Prediction and Residual Coding  Motion-Compensated Prediction  Spatial Intra Prediction  Variable Block-Size Spatial Transforms and Quantization  Internal Bit Depth Increase  In-Loop Filtering  Entropy Coding  Encoder Control  Coding Conditions and Results

Motion-Compensated Prediction  Fractional-Sample Interpolation Using MOMS  Generalized interpolation using MOMS  Choice of MOMS basis functions  Implementation aspects of cubic and quintic O- MOMS  Interleaved Motion-Vector Prediction  Merging of Motion-Compensated Predicted Blocks

 each MCP block is associated with one or two sets of motion parameters, where each set of motion parameters consists of a picture reference index and a translational motion vector.

Generalized interpolation using MOMS  Generating the prediction signal for motion vectors not pointing to an integer-sample position requires the use of a fractional-sample interpolation method  8-tap or 12-tap filters

Choice of MOMS basis functions  For our application case of fractional-sample interpolation, we have considered two members of the family of so-called O-MOMS (optimal MOMS) with interpolation kernels of degree L = 3 (cubic) and L = 5 (quintic).

Implementation Aspects of Cubic and Quintic O-MOMS  The prefiltering step can be efficiently realized by separably applying a discrete 1-D IIR filter along rows and columns of the reconstructed picture. In the case of cubic or quintic O- MOMS, this IIR filter can be factorized into one or two sets of first-order causal and anti-causal recursive filters, respectively.

Interleaved Motion-Vector Prediction  In order to reduce the bit rate required for transmitting the motion vectors  first step, the vertical motion vector component is predicted using conventional median prediction  Then, only those motion vectors of neighboring blocks for which the absolute difference between their vertical component and the vertical component for the current motion vector is minimized are used for the prediction of the horizontal motion- vector component

Merging of Motion-Compensated Predicted Blocks  However, in general, quadtree-based block partitioning may result in an over-segmentation due to the fact that, without any further provision, at each interior node of a quadtree, four subblocks are generated while merging of blocks is possible only by pruning complete branches consisting of at least four child nodes in the parent- child relationship within a quadtree.

outline  Overview of the Video Coding Scheme  Picture Partitioning for Prediction and Residual Coding  Motion-Compensated Prediction  Spatial Intra Prediction  Variable Block-Size Spatial Transforms and Quantization  Internal Bit Depth Increase  In-Loop Filtering  Entropy Coding  Encoder Control  Coding Conditions and Results

Spatial Intra Prediction  For all prediction block sizes, eight directional intra-prediction modes and one additional averaging (DC) mode are available.

outline  Overview of the Video Coding Scheme  Picture Partitioning for Prediction and Residual Coding  Motion-Compensated Prediction  Spatial Intra Prediction  Variable Block-Size Spatial Transforms and Quantization  Internal Bit Depth Increase  In-Loop Filtering  Entropy Coding  Encoder Control  Coding Conditions and Results

Variable Block-Size Spatial Transforms and Quantization  each prediction block can be further subdivided for the purpose of transform coding with the subdivision being determined by the corresponding RQT. Transform block sizes in the range of 4 × 4 to 64 × 64  The transform kernel for each supported transform block size is given by a separable integer approximation of the 2-D type-II discrete cosine transform of the corresponding block size

outline  Overview of the Video Coding Scheme  Picture Partitioning for Prediction and Residual Coding  Motion-Compensated Prediction  Spatial Intra Prediction  Variable Block-Size Spatial Transforms and Quantization  Internal Bit Depth Increase  In-Loop Filtering  Entropy Coding  Encoder Control  Coding Conditions and Results

Internal Bit Depth Increase  The internal bit depth d i for generating the prediction signal  bit depth do of luma and chroma samples of the original input video signal.  d s = d i − d o  increased internal bit depth d I Original input:do di bit for prediction do:in-loop filter

outline  Overview of the Video Coding Scheme  Picture Partitioning for Prediction and Residual Coding  Motion-Compensated Prediction  Spatial Intra Prediction  Variable Block-Size Spatial Transforms and Quantization  Internal Bit Depth Increase  In-Loop Filtering  Entropy Coding  Encoder Control  Coding Conditions and Results

In-Loop Filtering  Our proposed video coding scheme utilizes two types of cascaded in-loop filters:  Deblocking filter  The filtering operations are applied to samples at block boundaries of the reconstructed signal  Quadtree-Based Separable 2-D Wiener Filter  The quadtree-based Wiener filter as part of our proposed video coding approach, is designed as a separable filter with the advantage of providing a better tradeoff in computational cost versus rate-distortion (R-D) performance compared to nonseparable Wiener filters

outline  Overview of the Video Coding Scheme  Picture Partitioning for Prediction and Residual Coding  Motion-Compensated Prediction  Spatial Intra Prediction  Variable Block-Size Spatial Transforms and Quantization  Internal Bit Depth Increase  In-Loop Filtering  Entropy Coding  Encoder Control  Coding Conditions and Results

Entropy Coding  Probability Interval Partitioning Entropy Coding  PIPE Coding Using Arithmetic Codes  PIPE Coding Using V2V Codes

Entropy Coding(cont.)  Binary arithmetic decoding can be parallelized

outline  Overview of the Video Coding Scheme  Picture Partitioning for Prediction and Residual Coding  Motion-Compensated Prediction  Spatial Intra Prediction  Variable Block-Size Spatial Transforms and Quantization  Internal Bit Depth Increase  In-Loop Filtering  Entropy Coding  Encoder Control  Coding Conditions and Results

Encoder Control  the number of possible partitionings for prediction alone  exceeds 2 4 D − 1  and thus, for a more realistic configuration with  an CTB size of 64 × 64 and D = 4, more than 2 64 partitionings  need to be considered for selecting the optimal one. At least  for this example, a brute force exhaustive search is clearly not  feasible.

 Application of a Fast Optimal Tree Pruning Algorithm  G-BFOS algorithm  Mode Decision Process  Residual Quadtree Pruning Process

outline  Overview of the Video Coding Scheme  Picture Partitioning for Prediction and Residual Coding  Motion-Compensated Prediction  Spatial Intra Prediction  Variable Block-Size Spatial Transforms and Quantization  Internal Bit Depth Increase  In-Loop Filtering  Entropy Coding  Encoder Control  Coding Conditions and Results

 we used for the generation  of our submitted CS 1 bitstreams a hierarchical B picture  coding structure [37] with 4 layers and a corresponding intra  frame period. For CS 2, a structural delay is not allowed  and random access capabilities are not required

 fixed CTB size of  64 × 64 (for luma) and a maximum prediction quadtree depth  of D = 4.

Coding Conditions and Results