Fringe benefits of the H.264/AVC

2010 IEEE International Conference on Image Processing

2010

Self Cite

This paper proposes a hybrid approximate pattern matching/ transform-based compression engine. The idea is to use regular video interframe prediction as a pattern matching algorithm that can be applied to document coding. We show that this interpretation may generate residual data that can be efciently compressed by a transform-based encoder. The novelty of this approach is demonstrated by using H.264/AVC, the newest video compression standard, as a high quality book compressor. The proposed method uses segments of the originally independent scanned pages of a book to create a video sequence, which is encoded through regular H.264/AVC. Results show that the proposed method outperforms AVC-I (H.264/AVC operating in pure intra mode) and JPEG2000 by up to 4 dB and 7 dB, respectively. Superior subjective quality is also achieved.

Section: The Proposed Methodsmentioning

confidence: 99%

High quality scanned book compression using pattern matching

Zaghetto

2010 IEEE International Conference on Image Processing

2010

Self Cite

“…Image and video processing are driving forces behind this computational power pursuit. The state-of-the-art video compression standard, H.264/AVC [1]- [3], is a computation-hungry application. Nevertheless, energy usage and carbon emissions are a major concern today.…”

Section: Introductionmentioning

confidence: 99%

“…"Soccer" is present in the training and in the evaluation steps; however, the frames used to evaluate the encoder are from a different set from those used to build the training sequence 3. "Seq15" and "Seq21" are scenes where there is a couple of speakers on a table: the background is plain on "Seq15" and is detailed on "Seq21".…”

mentioning

confidence: 99%

Energy-constrained real-time H.264/AVC video coding

Fonseca

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

2013

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Energy consumption has become a leading design constraint for computing devices in order to defray electric bills for individuals and businesses. Over the past years, digital video communication technologies have demanded higher computing power availability and, therefore, higher energy expenditure. In order to meet the challenge to provide software-based video encoding solutions, we adopted an open source software implementation of an H.264 video encoder, the x264 encoder, and optimized its prediction stage in the energy sense (E). Thus, besides looking for the coding options which lead to the best coded representation in terms of rate and distortion (RD), we constrain the process to fit within a certain energy budget. i.e., an RDE optimization. We considered energy as the time integration of the real demanded electric power for a given system. We present an RDE-optimized framework which allows for software-based real-time video compression, meeting the desired targets of electrical consumption, hence, controlling carbon emissions. We show results of energy-constrained compression wherein one can save as much as 35% of the energy with small impact on RD performance.

“…Examples of continuous-tone image compression algorithm are JPEG [5] or JPEG2000 [6,7]. Some results point to the fact that the many coding advances brought into H.264/AVC operating in pure intra mode also made it a formidable compressor for still images [8,9,10]. Multilayer approaches such as the mixed raster content (MRC) imaging model [11,12,13,14,15] are also challenged by soft edges in scanned documents, often requiring pre-and post-processing [16].…”

Section: Introductionmentioning

confidence: 99%

HEVC-based scanned document compression

Zaghetto

Macchiavello

2012 19th IEEE International Conference on Image Processing

2012

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This paper proposes a hybrid pattern matching/transform-based compression engine for scanned compound documents. The novelty of this approach is demonstrated by using a modified version of the HEVC (High Efficiency Video Coding) Test Model as a compound document compressor, here conveniently referred to as HEDC (High Efficiency Document Coder). The proposed method uses segments of a document to create a video sequence, which is then encoded by HEDC. The idea is to explore interframe prediction as a pattern matching algorithm for coding units pre-classified as text; and intraframe prediction for coding units pre-classified as image. Results show that HEDC outperforms AVC-I, HEVC-I (H.264/AVC and HEVC operating in pure intra mode), H.264/AVC and JPEG2000 by up to 3.3, 2.5, 1.7 and 5 dB, respectively. Furthermore, for most documents the proposed method yields practically the same rate-distortion performance as regular HEVC, but is approximately 5% to 20% faster due to a pre-classification algorithm that prevents it of performing all possible inter/intra prediction tests for each prediction unit.