Improving MPEG-4 coding performance by jointly optimising compression and blocking effect elimination

Cheung, Wan-Fung; Chan, Yuk‐Hee

doi:10.1049/ip-vis:20010310

Cited by 6 publications

(3 citation statements)

References 17 publications

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“…Of particular interest to this study is the work of Campbell et al at University of Bristol, by which neural nets have been developed that can segment and recognize image regions in still or video imagery according to spectral (color) and textural (variance) criteria [18]. Such segmentation can be carried out a multiple resolution levels, and can be guided by information from a preprocessing compression stage such as JPEG, MPEG, or JPEG-2000 [5][6][7], where compressed blocks contain color, variance, or motion information.…”

Section: Principles Of Object-based Compressionmentioning

confidence: 99%

<title>Techniques for region coding in object-based image compression</title>

Schmalz

2004

SPIE Proceedings

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Object-based compression (OBC) is an emerging technology that combines region segmentation and coding to produce a compact representation of a digital image or video sequence. Previous research has focused on a variety of segmentation and representation techniques for regions that comprise an image. The author has previously suggested [1] partitioning of the OBC problem into three steps: (1) region segmentation, (2) region boundary extraction and compression, and (3) region contents compression. A companion paper [2] surveys implementationally feasible techniques for boundary compression.In this paper, we analyze several strategies for region contents compression, including lossless compression, lossy VPIC, EPIC, and EBLAST compression, wavelet-based coding (e.g., JPEG-2000), as well as texture matching approaches. This paper is part of a larger study that seeks to develop highly efficient compression algorithms for still and video imagery, which would eventually support automated object recognition (AOR) and semantic lookup of images in large databases or highvolume OBC-format datastreams. Example applications include querying journalistic archives, scientific or medical imaging, surveillance image processing and target tracking, as well as compression of video for transmission over the Internet. Analysis emphasizes time and space complexity, as well as sources of reconstruction error in decompressed imagery.

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Section: Principles Of Object-based Compressionmentioning

confidence: 99%

<title>Techniques for region coding in object-based image compression</title>

Schmalz

2004

SPIE Proceedings

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“…Actually, it is the most annoying artifact incurred by the block-based coding. Various postprocessing and pre-processing algorithms [16] are proposed to eliminate the blocking artifact such as overlapped motion compensation (OBMC) [17], projection onto convex sets (POCS) [18], maximum a posterior (MAP) [19], boundaryfiltering [20], filtering in transform domain [21] and so on. To make the computational cost as small as possible, the deblocking process is optional to all previous standards, and therefore is put outside the major coding loop.…”

Section: In-loop Deblockingmentioning

confidence: 99%

The optimization of H.264/AVC baseline decoder on low-cost TriMedia DSP processor

Wang

Yang

Tung

et al. 2004

Applications of Digital Image Processing XXVII

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The emerging video coding standard, H.264/AVC, exhibits the unprecedented coding performance. Comparing to traditional coders, e.g., MPEG-2 and MEPG-4 ASP, about half bitrate saving is shown in the official verification test. Such outstanding performance makes it become the video compression candidate for the upcoming HD-DVD. As a side effect, it was also blamed that H.264/AVC is much more logically complex and requires more computation power than any of the existing standards. A low-cost and efficient implementation of the international standard hence plays an important role of its success. In this paper, we realize an H.264/AVC baseline decoder by a low-cost DSP processor, i.e., Philips' TriMedia TM-1300, and illustrate that less computation demand for H.264/AVC decoding becomes feasible by using effective software core. To this end, we first consider different approaches and take advantage of SIMD instruction set to optimize critical time-consuming coding modules, such as the fractional motion compensation, spatial prediction and inverse transform. Next, we also present some other optimization approaches for entropy decoding and in-loop deblocking filtering, even though they cannot get benefits from utilizing SIMD. In our experiments, by exploiting appropriate instruction level parallelism and efficient algorithms, the decoding speed can be improved by a factor of 8~10; a CIF video sequence can be decoded at up to 19.74~28.97 fps on a 166-MHz TriMedia TM-1300 processor compared to 2.40~2.98 fps by the standard reference software.

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“…Actually, it is the most annoying artifact incurred by blockbased coding. Therefore, various post-processing and pre-processing algorithms [4] are proposed to eliminate the blocking artifact such as overlapped motion compensation (OBMC) [5], lapped orthogonal transform (LOT) [6], projection onto convex sets (POCS) [7], maximum a posterior (MAP) [8], block boundary filtering [9], filtering in transform domain [10]. While some video coding standards regard the deblocking filter as an optional post-processing, H.264/AVC makes it mandatory.…”

Section: Introductionmentioning

confidence: 99%