H.264/AVC到HEVC高效转码：基于预测同质性的优化策略

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本文主要探讨了"有效的基于预测同质性的H.264/AVC到HEVC转码器"这一主题。随着High Efficiency Video Coding (HEVC)标准的推出，旨在取代广泛使用的H.264/AVC标准，大量的已编码为H.264/AVC的遗产内容需要高效转码处理。H.264/AVC编码中包含的残差信息和运动信息是关键，这篇论文提出了一种利用这些信息的快速转码算法。作者深入分析了利用残差和运动信息时，视频区域的同质性特征。他们提出了一个结合区域预测同质性和当前编码信息的高效编码单元(CU)和预测单元(PU)决策策略。通过这种方法，该转码方案能够根据区域内像素的相似度，有效地划分和编码，从而减少冗余操作，提高编码效率。实验结果显示，与全解码再编码的方案相比，提出的转码策略能够在保持编码效率的同时，节省高达55%的编码时间。这种改进在很大程度上得益于对视频数据结构的理解和对预测同质性原则的有效应用，使得在转换过程中能更精准地进行区域分割和编码决策，显著提升了转码的性能和速度。本文的贡献在于提供了一种创新的转码技术，它在处理从H.264/AVC到HEVC的转换时，兼顾了编码效率和速度，对于现有的视频内容库升级和未来视频压缩技术的发展具有重要的实际价值。这对于IT行业来说，特别是在视频处理和编码优化方面，是一个重要的技术突破，有助于推动行业向更高效、低能耗的方向发展。

Effective H.264/AVC to HEVC Transcoder based on

Prediction Homogeneity

Fei

yang Zheng, Zhiru Shi, Xiaoyun Zhang, Zhiyong Gao

Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai, China

{zhfysheep, zhiru.shi, xiaoyun.zhang, zhiyong.gao}@sjtu.edu.cn

Abstract—The new video coding standard, High Efficiency

Video Coding (HEVC), has been established to succeed the

widely used H.264/AVC standard. However, an enormous

amount of legacy content is encoded with H.264/AVC. This

makes high performance AVC to HEVC transcoding in great

need. This paper presents a fast transcoding algorithm based on

residual and motion information extracted from H.264 decoder.

By exploiting these side information, regions’ homogeneity

characteristic are analysed. An efficient coding unit (CU) and

prediction unit (PU) mode decision strategy is proposed combing

regions’ prediction homogeneity and current encoding

information. The experimental results show that the proposed

transcoding scheme can save up to 55% of encoding time with

negligible loss of coding efficiency, when compared to that of the

full decoding and full encoding transcoder.

Index Terms

—HEVC, transcoding, fast partition decision,

residual homogeneity, motion homogeneity.

I. INTRODUCTION

H.264/AVC video coding standard has achieved great

success and been widely used for video streaming and storage.

Meanwhile, HEVC standard was standardized in 2013 to meet

the growing demands for ultra-high-definition videos

applications [1]. With more than 50% of encoding gains,

HEVC is expected to be the successor to H.264/AVC in the

near future. The demand for transcoding is rising, since large

amount of content encoded in H.264 can achieve better rate-

distortion performance by converting to HEVC format.

The H.264 to HEVC format transcoding is heterogeneous

transcoding, which mainly changes the bitstream format and

reduces the bitrate. Trivial solution is achieved by completely

decoding the source stream, and then completely re-encoding

it in the target format. This full decoding and full encoding

(FDFE) method can maximum the Rate-Distortion

performance, but not efficiency in terms of computational

complexity. This is the main problem faced by practical

H.264/AVC to HEVC transcoding service.

For transcoding, HEVC encoder is still using the block-

based hybrid coding framework, which is similar to

H.264/AVC. Many encoding sections are sharing similar

techniques, such as motion estimation, transform, quantization,

and entropy coding. It makes the fast H.264/AVC to HEVC

transcoding meaningful and possible. For the transcoder,

much information can be extracted from H.264/AVC decoder

to reduce HEVC encoding complexity and improve efficiency.

There are many features in the source bitstream which can be

used, such as motion vector (MV), mode information,

transform coefficients, CBP index and pixel residuals. The

key problem for fast transcoding is that how to effectively

explore these information to achieve a good trade-off between

RD performance and complexity reduction.

In the early works of transcoding, many solutions are

focused on making full use of motion vector information.

These solutions attempt to reduce the complexity of the ME

module in the codec. Motion vectors mapping and motion

refinement are applied to improve the motion estimation (ME)

[2] [3]. It is believed that fast ME and MV refinement make

less contribution in fast AVC-to-HEVC transcoding. This is

because the main complexity increasing of HEVC encoder is

coming from CU, PU and TU mode decision, which involve

large number of RDO computation. In this case, more

attentions are dropped on CU and PU partition mode decision.

To further reduce the transcoding complexity, a power

spectrum based rate-distortion optimization (PS-RDO) model

[4] is proposed for transcoding inter pictures. The cost of a

motion vector in the transcoder is calculated by MV variation

and power-spectrum of the prediction result. The PS-RDO

model is used to determine the CU partition, PU mode

decision and MV estimation. In [5], a metric named MV

variance distance (MVVD) is calculated, which is defined as

the square root of the variance of all collocated H.264/AVC

MVs in the CU area. Two thresholds, T

low

and T

high

, are

employed for the purpose of deciding whether the CU will be

split and which PU partitions will be searched. In [6], dynamic

thresholding is used to overcome the limitations of fixed

thresholds. Meanwhile another algorithm using content

modelling with linear discriminant functions (LDFs) is

proposed in [6]. Several features from H.264/AVC decoder

are gathered to conduct machine learning, such as, number of

H.264/AVC partitions, MV variance, non-zero coefficients

number and DCT coefficients energy. However, these

algorithms are not able to process the CUs containing intra

prediction blocks since MV information does not exist.

To overcome this disadvantage and fully use the prediction

information, a hybrid fast transcoding scheme is proposed in

this paper. A concept of prediction homogeneous

characteristic is raised not only to help making CU split

decision, but also to support fast PUs partition decision. By

exploring MV and residual information from H.264/AVC

decoder, the prediction homogeneity is determined for current

inter prediction coded block. The unnecessary CU and PU

partition candidates can be excluded efficiently. Since the

residual homogeneous can be obtained for both inter and intra

blocks, the proposed algorithm has a wider applicability.

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