Thesis Organization - 適用於高解析度靜態影像與視訊應用之H.264/MPEG-4 AVC框內編解碼器設計

Chapter 1 Introduction

1.2. Thesis Organization

This paper is organized with five parts. Chapter 1 gives the introduction and motivation of this work. Then in Chapter 2 , a brief overview of H.264/AVC standard and its intra coding is given. Chapter 3 presents an architecture design of H.264/AVC intra frame codec and the hardware oriented algorithm. In Chapter 4 a proposed intra frame encoder with fast prediction technique and lower working frequency is implemented. Finally a conclusion remark is given in Chapter 5 .

Chapter 2 Overview of H.264/AVC Standard

Earlier standards like MPEG-1 and MPEG-2 have enabled many popular consumer products such as video CDs and DVDs. As their successor, H.264/AVC is created more powerful in coding performance and more flexible in all kinds of applications. With the highly developed signal processing and semiconductor technology, many complicated and computationally intensive coding tools can be supported efficiently in H.264/AVC standard. These progressive tools have ability to improve the coding efficiency obviously but still maintain the decoded video quality.

2.1. Fundamental of H.264/AVC 2.1.1. Coding Structure

The coding structure of H.264/AVC is similar to those of previous standards and built on the commonly used motion estimation and transform coding structure. This standard supports the 4:2:0 format with 8-bit sample precision for pixel values and encodes the video by picture order. A picture, as well as an interlaced field or a non-interlaced frame, can be partitioned into several slices, and each slice consists of a series of macroblocks.

A macroblock is a primary unit for video coding and includes one 16x16 luminance (luma) and two 8x8 chrominance (chroma) components. The macroblock can further be separated into 16x8, 8x16, 8x8, 8x4, 4x8, and 4x4 sub-macroblocks for motion estimation/compensation, where the 4x4 one is called a block. The hierarchy of data organization in H.264/AVC is shown in Fig. 1.

Fig. 1 Hierarchy of video data components

Fig. 2 shows the basic structure diagram of H.264/AVC encoder, and Fig. 3 shows the decoder. The encoding flow first performs the intra prediction in I-slice or motion estimation in P-slice from some reference pictures. Residual values, the difference between predicted values and original ones, are then sent to forward transform unit and quantized after inter or intra prediction. The quantized coefficients, syntax, motion vectors, and other coding information are further coded by entropy coding. In addition, the quantized coefficients are also reconstructed through de-quantization, scaling, inverse transform, and motion compensation as the reference for next slice processing.

To decode a slice, residual values are recovered through entropy decoding, de-quantization, and inverse transform in proper order. Decoded slices can be reconstructed by adding residual values to established data from motion compensation for P-slice or intra mode prediction for I-slice. Detailed coding flow can refer to [1] or [4].

Entropy Coding Scaling & Inv.

Transform

Fig. 2 Basic structure diagram of H.264/AVC encoder

Scaling & Inv.

Transform

Fig. 3 Basic structure diagram of H.264/AVC decoder

2.1.2. Features of Standard

The H.264/AVC standard adopts many new coding tools which are never introduced in the earlier standards, and it also enhances previous techniques to obtain better coding

efficiency. These features significantly improve the coding performance and make the standard satisfy every technical application such as broadcast system and internet video.

Some of the important features in H.264/AVC are introduced in the following.

1. Variable block-size motion estimation and compensation

The standard has more flexibility in selection of block sizes and shapes for motion estimation and compensation than any previous standard. Seven kinds of block sizes are introduced, including 16x16, 16x8, 8x16, 8x8, 8x4, 4x8, and 4x4. This helps to enhance the efficiency of coding of irregularly shaped objects or background behind moving objects.

2. Quarter-sample-accurate motion vector

Most of the previous standards enable half-sample motion vector accuracy, but H.264/AVC improves it by adding quarter-sample motion vector accuracy, which is first found in the advanced profile of the MPEG-4 Visual (Part 2) standard. However, this standard further reduces the complexity of the interpolation processing to simplify the computation.

3. Multiple reference picture motion estimation and compensation

In MPEG-2 and its following standards, only one previous picture can be used to predict the values in the incoming picture. The H.264/AVC standard enlarges the selection range of reference pictures from one to more for better coding efficiency. Thus, motion vectors across multiple reference pictures are allowed. In addition, the standard also allows the bi-direction prediction coding which uses both previous and next pictures as reference ones.

4. Spatial-based directional intra prediction coding

In previous standards, such as MPEG-1 and MPEG-2, I-pictures are directly coded.

MPEG-4 Visual standard [3] adopts the Intra-AC and Intra-DC prediction for coding of I-pictures, which utilizes neighboring transformed blocks to perform the prediction and residual coding. However, these coding methods do not take advantage of the correlation among adjacent neighboring blocks. Thus, a spatial-based prediction technique with directional pixel mapping is presented in H.264/AVC for I-picture coding before transform, which uses the reconstructed neighboring pixels to perform the prediction with modes from different directions. With this technique, the coding efficiency for I-pictures can be improved effectively.

5. Small block size integer transform

All of the prior video standards use a transform block size of 8x8, while the new H.264/AVC uses a smaller transform size of 4x4. This allows the encoder to represent signals in a more locally-adaptive fashion and reduces the artifacts caused by the edges of different pixels.

6. In-loop deblocking filter

Block-based video coding may raise the blocking artifacts due to both prediction and residual difference coding of the decoding process. The solution to this problem is to use an adaptive deblocking filter which can improve the resulting video quality well.

Instead of building as an optical feature in H.263+, in H.264/AVC the deblocking filter is positioned in the motion compensation loop as an in-loop filter so that quality improvement in a single picture can be extended to the inter-picture prediction as well.

7. Context-adaptive entropy coding

For compression of quantized transform coefficients, an efficient variable-length coding (VLC) method is used in H.264/AVC. The VLC coding is previously used in the existing standards but enhanced in this standard with context adaptivity to increase the coding performance.

8. Arithmetic entropy coding

Another coding method known as context-adaptive binary arithmetic coding (CABAC) is also included in H.264/AVC as the advanced entropy coding. This arithmetic coding can achieve higher efficiency than VLC coding due to the effective probability model of symbol occurrence.

2.1.3. Profiles

Fig. 4 Three profiles of H.264/AVC

There are three profiles defined in H.264/AVC as shown in Fig. 4, which are baseline, main, and extended profiles. Baseline profile includes basic coding tools and features,

such as I-slice, P-slice, quarter-sample accurate motion vector, deblocking filter, and CAVLC, and is primarily used for lower-cost applications with demand of less computing resources. Thus, this profile is widely used in videoconferencing, internet multimedia, and mobile applications. Main profile is used as the mainstream consumer profile for applications of broadcast system and storage devices. It contains most of the features in baseline profile and other advanced techniques, like adaptive frame/field coding, interlaced coding, weighted prediction, B-slice, and CABAC. The main profile can achieve better performance in both bitrate saving and video quality while needs much more computation effort. Finally the extended profile, which includes all the features in baseline profile and main profile except CABAC, is intended as the streaming video profile and has relatively high compression capability with extra tricks for robustness to data losses and server stream switching.

2.2. Components of Baseline Intra Coding 2.2.1. Intra Prediction

Spatial-domain prediction is the main feature of H.264/AVC intra coding. There are two kinds of intra prediction for luma components, nine 4x4 prediction modes or four 16x16 prediction modes, which are shown in Fig. 5 and Fig. 6 respectively. The 4x4 prediction modes use the neighboring thirteen reconstructed samples denoted from A to M in Fig. 5 to predict the block pixels with eight different directions and one average value. For 16x16 prediction modes, the values are predicted from the 32 adjacent boundary pixels of upper and left macroblocks. Similar procedures are also applied to the chroma components where four 8x8 prediction modes are used with 16 neighboring pixels.

Fig. 5 Nine modes for intra 4x4 prediction

Fig. 6 Four modes for Intra 16x16 or 8x8 prediction

2.2.2. Cost Generation and Mode Decision

The best mode decision for intra prediction in [10] can be either the time consuming rate distortion optimization (RDO) or just much simpler cost accumulation. RDO uses the weighted sum of actual encoded bitrate and the reconstructed samples to produce distortion. Though it can achieve better performance, it is computationally intensive.

An alternative way is using cost accumulation. Two generally used mode decision methods for cost generation are available in [10], sum of absolute difference (SAD) and sum of absolute transform difference (SATD). The formulas are defined as follows.

) (

1 SAD 4m Qp

C = + λ (1)

) (

2 SATD 4m Qp

C = + λ (2)

In (1) and (2), symbol λ(Qp) stands for the lambda values which are from the approximated exponential function depending on the quantization parameters, and the variable m indicate whether the current mode is the most probable mode. If the most probable mode is detected, m is equal to 0, otherwise it sets to 1. The decision flow of most probable is illustrated in Fig. 7. In (3) and (4), sij and pij are the (i, j)th elements of source block and predicted block respectively. The function T(x) in (4) represents the 4x4 discrete Hadamard transform (DHT), as shown in (5), where symbol X indicates the residual block.

Find upper and left block modes

Boundary block?

Most probable

= DC mode

Fig. 7 Flow diagram of most probable mode selection

For every four blocks in Z-scan order of a macroblock, another lambda value, 6λ (Qp)+0.5, is added to cost value for adjusting the weight. The best mode is finally

decided by comparing the summarized cost value of sixteen blocks in the 4x4 prediction to the best mode of the 16x16 prediction.

2.2.3. Transform

In H.264/AVC, a traditional 8x8 floating-point discrete cosine transform (DCT) in previous standards is replaced by an approximated 4x4 DCT. The transform can be divided into two parts, 4x4 integer transform and fractional scalar multiplication factors that are further merged into the quantization stage. The forward 4x4 integer transform with quantization is illustrated in (6), and the inverse one with de-quantization is illustrated in (7). In which, the matrices with factors a and b denote the scalar multiplication. Notice that matrix X in (6) is post-scaled by quantization and matrix Y in (7) is pre-scaled by de-quantization. For a macroblock predicted by the 16x16 or 8x8 modes, the DC value of each transformed block is further processed by 4x4 DHT or 2x2 DHT respectively, as shown in (5) or (8)

⎥⎥

In the quantization stage, there are 52 values of quantization parameters (QPs) and corresponding quantization steps supplied in H.264/AVC standard. The steps are doubled for increase of every six numbers in QPs. The scaling factors mentioned in Subsection 2.2.3 are incorporated into these quantization factors to avoid the computational complexity in 4x4 transform stage. These factors for quantization and de-quantization are implemented in [10] as a multiplication factors and shown in Table 2 and Table 3 respectively.

Table 2 Quantization factors in H.264/AVC

Table 3 De-quantization factors in H.264/AVC

2.2.5. Entropy Coding

There are two entropy coding methods supported in H.264/AVC baseline profile.

1. Exp-Golomb coding

The standard uses the exponential Golomb coding (Exp-Golomb) to encode the syntax elements of coding information, such as mode and type. Exp-Golomb codes consist of a prefix part and a suffix part with a string of bits as shown in Fig. 8. The signed values of syntax elements are assigned to the unsigned code number for code mapping.

Bitstring Code Num Code Num Syntax Value

1 0 0 0

Bitstring Form Range 0 1 0 1 1 1

1 0 0 1 1 2 2 -1

0 1 x1 1 - 2 0 0 1 0 0 3 3 2

0 0 1 x1 x0 3 - 6 0 0 1 0 1 4 4 -2

0 0 0 1 x2 x1 x0 7 - 14 0 0 1 1 0 5 5 3

0 0 0 0 1 x3 x2 x1 x0 15 - 30 0 0 1 1 1 6 6 -3

0 0 0 0 0 1 x4 x3 x2 x1 x0 31 - 62 0 0 0 1 0 0 0 7 7 4

… … … … … …

(a) (b) (c)

Fig. 8 (a) Prefix and suffix bitstrings, (b) exp-Golomb bitstrings, (c) mapping for signed bitstrings

2. Context adaptive variable length coding (CAVLC)

In baseline profile, the standard uses CAVLC for coding the quantized samples to bitstream. Fig. 9 illustrates an example of CAVLC coding in flow diagram. The following items are coded in a proper order: number of nonzero coefficients, sign marks of trailing ones, levels of remaining nonzero coefficients, number of total zeros, runs of zeros between nonzero coefficients. The coefficients should be scanned in the reversed zigzag order for CAVLC coding, but for decoding, the process is the reverse of the encoding one. If all coefficients within an 8x8-size block are zero, the coding process will skip them and assign a special flag, coded block pattern (CBP), to denote such case.

Fig. 9 Example of CAVLC Coding

Chapter 3 H.264/AVC Intra Frame Codec

H.264/AVC is popularly regarded as the video standard in the next generation to replace the existing MPEG-2 standards. The spatial-domain intra coding is a newly supported technique which is not only suitable for moving video coding but also still image compression. However, the common digital signal processors are hard to afford its high computational complexity and large data throughput.

In this chapter, a parallel H.264/MPEG-4 AVC baseline profile intra frame codec supporting both processes of encoder and decoder is proposed for digital camera and video application. This work is mainly based on the previous architecture [11] and modified to fit the decoding procedure. The proposed chip has ability to support high definition (HD) size 720p (1280x720 4:2:0) at 30 fps real-time video encoding at 117MHz and 1080p (1920x1080 4:2:0) at 30 fps video decoding at 58MHz. When clocked at the height frequency 125MHz, this design can process encoding of 29.62M pixels still image per second or decoding of 135.60M pixels. The research result of this work is also published in [12].

3.1. Hardware Oriented Algorithm

3.1.1. Enhanced SATD Function for Mode Decision

In determining the coding performance of intra-only H.264/AVC, the cost function for mode decision is the most important part. To find a best matched prediction mode is to use RDO. Though RDO can provide the best performance, its complexity hinders its use in the hardware design. Thus, the SATD method is adopted to calculate the costs.

However, how to determine the transform for SATD computation will become the main issue now. The transform choice used in SATD should be computationally simple but also effective to estimate the energy of the signals. In [10], a pure transform of 4x4 DHT is adopted for mode decision, but it is far from the real transform used in the whole encoding process. A better transform choice for SATD shall approximate the effect of transform and quantization used in the H.264/AVC encoding process to estimate the real bitrate. Therefore, previous works [13][14] use the 4x4 integer transform as the choice. Although their approaches can achieve better performance than DHT does, it’s still not good enough. That is because that the fractional multiplication factors do not be taken into consideration. A complete transform function in H.264/AVC shall include both the integer transform and multiplication factors in the quantization formula as shown in (6) and (7). However, to incorporate these factors into the cost function directly will cost a lot of computation because they are not simple integer numbers. Besides, these factors cannot be directly derived from the formula since the quantization parameters shall also be included.

To solve these problems, this work adopts the cost function proposed in [11] that combines the integer transform and simplified multiplication factors. The simplified multiplication factors are derived from quantization coefficients shown in Table 2 and Table 3 . Derivation from the quantization coefficients enables the consideration of both effects of transform and quantization. From these tables, we can obtain the required scalar factors by approximating the relationship among the reciprocal of de-quantization coefficients and simplifying them to integers for reduction of computational complexity as shown in (9) and (10).

1/quant_coef: p(0,0)^-1 : p(0,1)^-1 : p(1,1)^-1~= 30:19:12 (9)

1/dequant_coef: p(0,0)^-1 : p(0,1)^-1 : p(1,1)^-1~= 30:25:20 (10) In (9) and (10) the symbol p(x,y) represents the quantization and de-quantization coefficients of different positions in Table 2 and Table 3 respectively. The scaling factors derived from the de-quantization table are adopted by considering the final performance and implementation cost, as shown in (11). In this formula, division by 32 is added to avoid enlargement of cost values, which can be carried out with simpler low-cost wiring in the hardware design. As a result, the cost generation function is able to estimate the energy of residuals after the transform and quantization function more accurate than other methods while still keep computation simple and suitability for hardware implementation. It can provide better quality than that in [10] and can be used to compensate the quality loss of the plane mode removal discussed in Subsection 3.1.2.

3.1.2. Intra Plane Mode Removal

The various intra prediction modes can further be organized systematically into four types according to their prediction properties and computational complexity. These types are illustrated in Fig. 10. The bypass type is easy to be implemented since the prediction samples are the same as boundary pixels. In the average type, neighboring eight pixels (for 4x4 prediction) or 32 pixels (for 16x16 prediction) are summarized and divided into an average value for all prediction samples. The linear type contains most of the 4x4 prediction modes with directional approach, and the samples are linearly interpolated by boundary pixels. Finally in the bilinear type, also known as plane prediction, samples are derived by the approximation of bilinear transform. Though

being simplified to be only integer arithmetic operations, the plane mode is still much more computational complex than other modes. Besides, it is also hard to reuse its results for other prediction, and occupies almost half of the area in the intra prediction unit. The detail computation of plane prediction can refer to Fig. 11.

Bypass

Linear

Average Bilinear

Fig. 10 Four categorized types of intra prediction modes

A solution to this problem is to eliminate the plane mode from intra prediction and replace it with other modes. This may raise the issue of performance loss. Table 4 shows the probability distribution of the 16x16 prediction modes in different sequences.

Macroblocks predicted in plane mode is only 4.2% in average and not larger than 5.7%

except the sequence “Akiyo” which contains much smoother texture. However, after simulation we found that prediction with plane mode only reduces about 1% of bitrate than that without plane mode for these video sequences. This 1% bitrate loss can be easily compensated by the enhanced cost function proposed in Subsection 3.1.1. With the modification, we can achieve almost the same result as [10] but save a lot of

computation and hardware cost.

Luma 16x16

h= Σx[ p(7+i,-1) - p(7-i,-1) ] i=1~8 v= Σy[ p(-1,7+i) - p(-1,7-i) ] i=1~8 a= 16*[ p(-1,15) + p(15,-1) ]

b= ( 5h+32 )>>6 c= ( 5v+32 )>>6

Pred= [ a + b(x-7) + c(y-7) + 16 ]>>5

Chroma 8x8

h= Σx[ p(4+i,-1) - p(4-i,-1) ] i=1~4 v= Σy[ p(-1,4+i) - p(-1,4-i) ] i=1~4 a= 16*[ p(-1,7) + p(7,-1) ]

b= ( 17h+16 )>>5 c= ( 17v+16 )>>5

Pred= [ a + b(x-3) + c(y-3) + 16 ]>>5

Fig. 11 Intra plane mode for (a) 16x16 (b) 8x8 predictions

Table 4 Probability distribution of 16x16 modes in different sequence with 300 I-frames at QP=28

Total ratio Veritical Horizontal DC Plane

Mobile 3.3% 0.8% 1.0% 1.3% 0.2%

Coastguard 10.7% 0.8% 3.8% 4.6% 1.6%

Stefan 20.7% 3.4% 12.8% 2.0% 2.5%

Paris 15.5% 3.2% 4.6% 4.4% 3.4%

Foreman 23.1% 5.1% 4.3% 8.0% 5.7%

Akiyo 47.5% 5.3% 4.8% 25.7% 11.8%

Sequence 16x16 modes

3.1.3. Simulation Results

Table 5 illustrates the comparison results for encoding of six CIF-size sequences with all intra frames in different QPs among four algorithms: the original SATD function in [10], SAITD algorithm in [14], enhanced SATD cost function, and the proposed method

combining enhanced function and plane mode removal. In most cases of the simulation, it is obvious that the proposed SATD cost function is able to achieve better coding efficiency than [10] and [14], with almost the same or even better PSNR quality. We can also observe that the enhanced algorithm can reduce average 0.08% bitrate for all sequences. After combining with technique of plane mode removal, the bitrate increase is compensated and not larger than 0.06% in average.

Table 5 Comparison among original code [10], SAITD algorithm in [14], and the two proposed algorithm for coding of 300 Intra frames

SNR Y SNR U SNR V Bit-rate SNR Y SNR U SNR V Bit-rate SNR Y SNR U SNR V Bit-rate SNR Y SNR U SNR V Bit-rate 16 46.38 47.27 47.43 10537.41 +0.10 +0.00 +0.00 +0.11% +0.06 +0.00 -0.01 -0.16% +0.06 +0.00 +0.00 -0.11%

20 42.96 44.43 44.51 8143.18 +0.05 -0.03 -0.03 +0.07% +0.02 -0.03 -0.03 -0.18% +0.02 -0.03 -0.03 -0.12%

24 39.63 41.63 41.65 6189.86 -0.02 -0.14 -0.13 +0.15% -0.04 -0.14 -0.13 -0.22% -0.04 -0.14 -0.12 -0.14%

28 36.41 38.95 38.96 4585.29 -0.02 -0.23 -0.24 +0.15% -0.05 -0.23 -0.24 -0.24% -0.05 -0.23 -0.25 -0.16%

32 33.05 37.12 37.08 3246.41 -0.05 -0.41 -0.43 +0.34% -0.08 -0.41 -0.43 -0.21% -0.08 -0.42 -0.45 -0.15%

36 29.96 35.15 35.07 2218.46 -0.06 -0.48 -0.52 +0.95% -0.10 -0.49 -0.52 -0.09% -0.11 -0.53 -0.55 -0.06%

16 45.93 46.25 46.29 15361.27 +0.04 +0.01 +0.01 +0.05% +0.04 +0.01 +0.01 -0.10% +0.04 +0.01 +0.01 -0.08%

20 42.14 42.87 42.89 12233.46 +0.05 -0.03 -0.04 +0.07% +0.03 -0.03 -0.04 -0.12% +0.03 -0.03 -0.03 -0.09%

24 38.49 39.72 39.68 9487.00 +0.01 -0.11 -0.10 +0.17% -0.01 -0.11 -0.10 -0.14% -0.01 -0.11 -0.10 -0.10%

28 35.04 36.88 36.76 7179.38 +0.03 -0.17 -0.18 +0.26% +0.01 -0.17 -0.18 -0.16% +0.01 -0.16 -0.18 -0.12%

32 31.50 34.89 34.67 5200.07 +0.02 -0.24 -0.24 +0.52% -0.01 -0.24 -0.24 -0.14% -0.01 -0.24 -0.23 -0.09%

36 28.28 32.87 32.60 3572.40 +0.01 -0.31 -0.32 +1.08% -0.05 -0.31 -0.22 -0.05% -0.05 -0.31 -0.22 +0.01%

16 46.16 47.35 47.63 10114.93 +0.08 -0.05 -0.05 +0.12% +0.06 -0.05 -0.05 -0.09% +0.06 -0.05 -0.04 -0.00%

20 42.81 44.69 44.88 7662.99 +0.02 -0.21 -0.16 +0.25% -0.01 -0.21 -0.16 -0.08% -0.01 -0.20 -0.15 -0.01%

24 39.59 41.97 42.12 5742.80 -0.05 -0.35 -0.28 +0.49% -0.09 -0.36 -0.28 -0.06% -0.09 -0.36 -0.28 +0.05%

28 36.49 39.40 39.54 4235.43 -0.05 -0.50 -0.34 +0.70% -0.20 -0.50 -0.34 -0.06% -0.10 -0.52 -0.36 +0.09%

32 33.33 37.51 37.73 3005.78 -0.14 -0.61 -0.52 +0.82% -0.20 -0.61 -0.52 -0.11% -0.20 -0.65 -0.52 +0.08%

36 30.36 35.58 35.78 2055.30 -0.18 -0.64 -0.54 +1.00% -0.25 -0.64 -0.55 -0.13% -0.25 -0.67 -0.56 +0.08%

16 47.34 48.46 49.40 4159.54 +0.16 -0.06 -0.11 +0.95% +0.09 -0.05 -0.12 -0.10% +0.10 -0.06 -0.12 +0.42%

20 44.89 46.88 47.95 2777.52 +0.04 -0.26 -0.33 +0.83% -0.05 -0.26 -0.34 -0.16% -0.05 -0.30 -0.38 +0.18%

24 42.65 44.62 46.03 1941.72 -0.14 -0.35 -0.58 +1.03% -0.23 -0.35 -0.58 +0.18% -0.25 -0.37 -0.64 +0.56%

28 40.33 42.52 43.93 1370.30 -0.18 -0.53 -0.77 +1.49% -0.33 -0.54 -0.76 +0.27% -0.35 -0.63 -0.85 +0.62%

32 37.77 40.82 42.54 963.42 -0.32 -0.53 -0.89 +1.71% -0.53 -0.52 -0.86 -0.66% -0.58 -0.69 -1.09 +0.30%

36 35.28 38.80 40.69 672.96 -0.38 -0.45 -0.78 +2.80% -0.65 -0.50 -0.75 +0.17% -0.70 -0.64 -0.98 +0.28%

16 46.26 47.56 48.57 7665.68 +0.10 +0.03 -0.01 +0.28% +0.08 +0.03 -0.01 -0.14% +0.08 +0.03 +0.00 -0.04%

20 42.90 45.17 46.83 5394.72 +0.13 -0.08 -0.21 +0.59% +0.09 -0.08 -0.21 -0.13% +0.09 -0.08 -0.21 -0.00%

24 39.95 42.87 44.78 3678.28 +0.04 -0.25 -0.33 +1.20% -0.03 -0.24 -0.33 -0.08% -0.03 -0.25 -0.35 +0.07%

28 37.26 40.91 42.79 2467.35 +0.03 -0.32 -0.42 +1.80% -0.06 -0.32 -0.42 -0.08% -0.06 -0.34 -0.46 +0.10%

32 34.61 39.80 41.32 1598.24 -0.05 -0.41 -0.54 +2.62% -0.19 -0.41 -0.54 +0.03% -0.20 -0.46 -0.60 +0.30%

36 32.24 38.61 39.81 1022.62 -0.08 -0.39 -0.49 +4.19% -0.31 -0.39 -0.49 -0.00% -0.32 -0.45 -0.57 +0.53%

16 45.88 48.20 49.05 9454.85 +0.04 +0.06 +0.05 +0.15% +0.04 +0.06 +0.05 -0.20% +0.04 +0.06 +0.05 -0.18%

20 42.13 46.38 47.64 6969.04 +0.10 -0.04 -0.10 +0.30% +0.09 -0.04 -0.10 -0.21% +0.09 -0.05 -0.11 -0.20%

24 38.74 44.64 46.13 4959.03 +0.08 -0.21 -0.12 +0.74% +0.06 -0.21 -0.11 -0.16% +0.06 -0.24 -0.13 -0.15%

28 35.63 43.08 44.72 3437.66 +0.15 -0.27 -0.15 +1.33% +0.12 -0.27 -0.15 -0.11% +0.12 -0.35 -0.18 -0.14%

32 32.74 41.96 43.72 2236.41 +0.06 -0.31 -0.17 +1.99% +0.00 -0.31 -0.16 -0.13% +0.00 -0.44 -0.23 -0.17%

36 30.24 40.82 42.72 1418.33 -0.04 -0.28 -0.11 +2.68% -0.15 -0.27 -0.11 -0.17% -0.14 -0.39 -0.14 -0.03%

Coastguard Akiyo

Foreman

JM 8.6 [9] Enhanced SATD Cost Function Enhanced SATD Cost Function + Plane

在文檔中適用於高解析度靜態影像與視訊應用之H.264/MPEG-4 AVC框內編解碼器設計 (頁 18-0)