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Category : KTA

Two Loop Filters in KTA

2010-08-01 KTA 1 Comment Views(9,750)

KTA employs two concatenating loop filters: the deblocking loop filter and the adaptive loop filter.
The deblocking loop filter, inherited from H.264/AVC, alleviates the blocking artifacts caused by the block-based DCT+MCP video coding framework. It uses a bank of low-pass filters, which are adaptively applied to block boundaries according to the boundary strength (BS), and provides better visual quality and improved capability to predict other pictures.
Adaptive loop filter (ALF; click here for introduction) is placed in the MCP loop after the deblocking process, and is used to restore the degraded picture (caused by compression) such that the MSE between the reconstructed and source frames is minimized. The coefficients of ALF are calculated and transmitted on a frame basis and the minimum mean squared error (MMSE) estimator is used. For each degraded frame, ALF can be applied to the entire frame or to local areas. The former is known as frame-based ALF. In the latter case, additiona[......]

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Adaptive Interpolation Filter for Video Coding

2010-07-21 KTA 2 Comments Views(15,666)

Why use interpolation in video coding?  
Motion-compensated prediction (MCP) is the key to the success of the modern video coding standards, as it removes the temporal redundancy in video signals and reduces the size of bitstreams significantly. With MCP, the pixels to be coded are predicted from the temporally neighboring ones, and only the prediction errors and the motion vectors (MV) are transmitted. However, due to the finite sampling rate, the actual position of the prediction in the neighboring frames may be out of the sampling grid, where the intensity is unknown, so the intensities of the positions in between the integer pixels, called sub-positions, must be interpolated and the resolution of MV is increased accordingly.  
Interpolation in H.264/AVC  
In H.264/AVC, for the resolution of MV is quarter-pixel, the reference frame is interpolated to be 16 times the size for MCP, 4 times both sides. As shown in Fig. 1(a), the interpolation defined in H.264 includes two stages, inter[......]

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Mode-Dependent Directional Transform (MDDT) in JM/KTA

2009-09-22 KTA 15 Comments Views(13,620)

The intra prediction in H.264/AVC is a type of spatial domain directional prediction, which means different intra prediction modes represent different prediction directions, such as horizontal, vertical, and diagonal. An intra-coded MB can be partitioned into 4×4, 8×8, or 16×16 intra prediction blocks. The 4×4 and 8×8 intra prediction blocks have nine prediction directions, respectively, and the 16×16 block has four. Hence, totally 22 (9+9+4) intra prediction modes are used in H.264/AVC. The residue usually has high energy along the direction of prediction, as edges are more difficult to be predicted than smooth areas.
Mode-dependent directional transform (MDDT) was proposed to compact the residue produced by intra prediction. It consists of a series of pre-defined separable transforms; each transform is efficient in compacting energy along one of the prediction directions, thus favoring one of the intra modes. The type of MDDT is coupled with the selected[......]

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Adaptive Post/Loop Filters in JM/KTA – Part 2

2009-08-23 KTA 12 Comments Views(17,109)

3. Adaptive Loop Filter
As far as adaptive loop filter (ALF) is concerned, there are three types of ALF: frame-based, block-based and quadtree-based ALFs. All of them are based on wiener filter, but with different filtering control basis. In frame-based ALF [VCEG-C437/AI14, C402], only one picture level flag is used to signal the decision of filtering or non-filtering.
Although wiener filter can restore the reconstructed picture to the original picture globally, there are degraded pixels locally. Since the degraded area reduce the filtering efficiency, if these areas are not filtered, the capabilities of picture restoration and loop filtering are improved. Therefore, block-based ALF [VCEG-AI18/AJ13] use explicit flags for filtering on-off on block by block basis, while quadtree-based ALF [VCEG-C181/AK22] introduces a quadtree data structure to carry out the variable-size block filtering.
3.1 Block-based Adaptive Loop Filter
Block-based ALF is an improvement of frame-based ALF. Figure 2[......]

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Adaptive Post/Loop Filters in JM/KTA – Part 1

2009-08-22 KTA Post Comment Views(7,495)

1. Introduction
The basic idea of adaptive post/loop filter is the same. Both of them use adaptive wiener filtering technique to improve the quality of reconstructed picture which is degraded by compression. The difference between them is whether the filtering process is applied in or out of the core coding loop, as shown in Figure 1,  to improve the quality of reconstructed picture or just displayed picture.
Figure 1. Block diagram of JM/KTA
2. Adaptive Post Filter
In H.264/AVC, there is already an existing post-filter hint SEI message [JVT-S030/T039/U035] which provides the coefficients of a post-filter or correlation information for the design of a post-filter for potential use in post-processing of the output decoded pictures to obtain improved displayed quality.
To find the coefficients of adaptive wiener filter, the following cost function based on the whole frame is minimized:
Eq1 (1)
where R is the reconstructed picture, R’ is the filtered picture, and I is the original pic[......]

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Quantization Techniques in JM/KTA – Part 4

2009-06-21 KTA Post Comment Views(9,506)

4. Rate-Distortion Optimized Quantization
Previously, adaptive rounding was proposed to improve quantization, which captures the statistics of the incoming residual signal and adjusts the rounding offsets accordingly. However, the adaptive rounding quantization is still based on the criterion which minimizes the mean-squared quantization error between the original signal and the quantization reconstructed signal. From the sense of rate-distortion optimization, the cost from the rate should also be considered.
The basic idea underlying the rate-distortion optimized quantization is to minimize a cost function D+ λR such that both the rate R and the distortion D are considered in coding decisions. For quantization case, the RD optimal coding is to solve a minimization problem of
where S is the original signal, and T-1 denotes the inverse transform operation. Consider that the DCT is a unitary transform, which maintains the Euclidean d[......]

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Quantization Techniques in JM/KTA – Part 3

2009-06-21 KTA 2 Comments Views(5,782)

3. Adaptive Rounding Encoding Technique using an Equal Expected-Value Rule
As discussed above, if the input p.d.f. is Laplacian distributed and if we can estimate λ, then the optimal f can be found analytically. But, usually the estimate of input p.d.f. is not available, then, how to select the rounding offset f?
In order to select rounding offset f adaptively, an adaptive quantization encoding technique using an equal expected-value rule is proposed by Gary Sullivan from Microsoft. The adaptive adjustment of the rounding offset f occurs only in the encoding quantization process, which tries to select f without using any priori model knowledge on the input W. The aim is to make that the mean of the absolute value of the input, |W|, is equal to its expected reconstruction value |W’|, i.e.,
Any values in an interval would be reconstructed to some W’, so the distribution of W’ is a probability ma[......]

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Quantization Techniques in JM/KTA – Part 2

2009-06-21 KTA Post Comment Views(7,454)

2. Principle of H.264/AVC Normal Quantization Scheme
2.1. Scalar dead-zone quantization
In this section the principle of H.264/AVC normal quantization scheme is described in a generalized form.
A scalar quantizer for input signal W can be decomposed into a function Z=C[W] called a classification rule that selects an integer-valued class identifier called the quantization index at the encoder, and a reconstruction rule that produces a real-valued output W’=R[Z] at the decoder. Video encoder applies entropy coding to the quantization indices and communicates to the decoder. Although H.264/AVC JM reference software implements some classification functions, only reconstruction function is standardized.
In the quantization step of the encoder, the transform coefficients of the prediction error are quantized. This quantization is used to reduce the precision of the coefficients. Furthermore, the quantizer is designed to map insignificant coefficient values to zero whilst retaining a reduced [......]

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