Low-complexity transform and quantization in H.264/AVC

Malvar, H.S.; Hallapuro, A.; Karczewicz, Marta; Kerofsky, Louis

doi:10.1109/tcsvt.2003.814964

Cited by 565 publications

(251 citation statements)

References 3 publications

Supporting

Mentioning

250

Contrasting

Unclassified

Order By: Relevance

“…In Intra mode, PRED is formed from spatially neighboring samples in the current slice that have previously been encoded, decoded and reconstructed (uF'n in the figure1 note that unfiltered samples are used to form PRED). The encoding process chooses which and how neighboring samples are used for Intra prediction, which is simultaneously conducted at the encoder and decoder using the transmitted Intra prediction side information (Malvar et al, 2003). In Inter mode, PRED is formed by motion-compensated prediction from one or multiple reference picture(s) selected from the set of reference pictures.…”

Section: Fig 1 H264 /Avc Video Encoder Block Diagrammentioning

confidence: 99%

See 1 more Smart Citation

Complexity/Performance Analysis of a H.264/AVC Video Encoder

Zrida¹,

Ammari²,

Abid³

et al. 2011

Recent Advances on Video Coding

View full text Add to dashboard Cite

Section: Fig 1 H264 /Avc Video Encoder Block Diagrammentioning

confidence: 99%

“…One of 52 quantizers is selected for each macroblock by the Quantization Parameter (QP). The quantizers are arranged so that there is an increase of approximately 12.5% in the quantization step size when incrementing the QP by one (Malvar et al, 2003).…”

Section: Main Innovations In Comparison To Previous Standardsmentioning

confidence: 99%

Complexity/Performance Analysis of a H.264/AVC Video Encoder

Zrida¹,

Ammari²,

Abid³

et al. 2011

Recent Advances on Video Coding

View full text Add to dashboard Cite

“…where C i represents the inverse H.264/AVC integer transform [4]. A traditional forward 8×8 DCT transform is applied to a group of four 4×4 blocks…”

Section: Residual Data Mappingmentioning

confidence: 99%

Dyadic spatial resolution reduction transcoding for H.264/AVC

et al. 2010

View full text Add to dashboard Cite

In this paper, we examine spatial resolution downscaling transcoding for H.264/AVC video coding. A number of advanced coding tools limit the applicability of techniques which were developed for previous video coding standards. We present a spatial resolution reduction transcoding architecture for H.264/AVC, which extends open-loop transcoding with a low-complexity compensation technique in the reduced-resolution domain. The proposed architecture tackles the problems in H.264/AVC and avoids visual artifacts in the transcoded sequence, while keeping complexity significantly lower than more traditional cascaded decoder-encoder architectures. The refinement step of the proposed architecture can be used to further improve rate-distortion performance, at the cost of additional complexity. In this way, a dynamiccomplexity transcoder is rendered possible. We present a thorough investigation of the problems related to motion and residual data mapping, leading to a transcoding solution resulting in fully compliant reduced-size H.264/AVC bitstreams.

show abstract

“…For transformation, the H.264/AVC integer transform (Malvar, 2003) is used as a computationally efficient approximation of the DCT. Each transform coefficient is uniformly quantized in the same way, using one of six available quantization patterns, resulting in quantized coefficients consisting of 8-3 bits.…”

Section: Transformation and Quantizationmentioning

confidence: 99%

Distributed Video Coding for Video Communication on Mobile Devices and Sensors

Lambert

Mys

Škorupa

et al. 2010

Handheld Computing for Mobile Commerce

View full text Add to dashboard Cite

In the context of digital video coding, recent insights have led to a new video coding paradigm called Distributed Video Coding, or DVC, characterized by low-complexity encoding and highcomplexity decoding, which is in contrast to traditional video coding schemes. This chapter provides a detailed overview of DVC by explaining the underlying principles and results from information theory and introduces a number of application scenarios. It also discusses the most important practical architectures that are currently available. One of these architectures is analyzed step-by-step to provide further details of the functional building blocks, including an analysis of the coding performance compared to traditional coding schemes. Next to this, it is demonstrated that the computational complexity in a video coding scheme can be shifted dynamically from the encoder to the decoder and vice versa by combining conventional and distributed video coding techniques. Lastly, this chapter discusses some currently important research topics of which it is expected that they can further enhance the performance of DVC, i.e., side information generation, virtual channel noise estimation, and new coding modes.

show abstract

Low-complexity transform and quantization in H.264/AVC

Cited by 565 publications

References 3 publications

Complexity/Performance Analysis of a H.264/AVC Video Encoder

Complexity/Performance Analysis of a H.264/AVC Video Encoder

Dyadic spatial resolution reduction transcoding for H.264/AVC

Distributed Video Coding for Video Communication on Mobile Devices and Sensors

Contact Info

Product

Resources

About