Fast mode decision algorithm for scalable video coding based on luminance coded block pattern

Kim, Taejung; Yoo, Jeong-Ju; Hong, Jin‐Woo; Suh, Jae-Won

doi:10.1117/1.oe.52.1.017401

Cited by 3 publications

(2 citation statements)

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“…The employed test platform was Intel (R), with 3.40 GHz CPU, 8 GB RAM, in the Windows XP Professional operating system. The experimental results of the proposed algorithms were variously compared with those of the JSVM reference software, Tae algorithm [11], and Seon-2 algorithm [13]. All the results were expressed as percentages relative to those of the reference software.…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…Shen et al [4] suggested two techniques for mode decision, namely, skip mode decision and adaptive early termination, which utilize both coding information on spatial neighbor macroblocks (MBs) within the same frame and neighbor MBs in the BL. Kim et al [11] described an algorithm based on a 16 × 16 coded block pattern (CBP) mode in the current frame and the best CBP mode in the selected reference frame. Li et al [12] developed an algorithm based on the distribution relationship between the BL and EL.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Enhancement for Spatial Scalable Video Coding Transmission

Khairy

Hamdy

Elsayed

et al. 2017

Mathematical Problems in Engineering

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Scalable Video Coding (SVC) is an international standard technique for video compression. It is an extension of H.264 Advanced Video Coding (AVC). In the encoding of video streams by SVC, it is suitable to employ the macroblock (MB) mode because it affords superior coding efficiency. However, the exhaustive mode decision technique that is usually used for SVC increases the computational complexity, resulting in a longer encoding time (ET). Many other algorithms were proposed to solve this problem with imperfection of increasing transmission time (TT) across the network. To minimize the ET and TT, this paper introduces four efficient algorithms based on spatial scalability. The algorithms utilize the mode-distribution correlation between the base layer (BL) and enhancement layers (ELs) and interpolation between the EL frames. The proposed algorithms are of two categories. Those of the first category are based on interlayer residual SVC spatial scalability. They employ two methods, namely, interlayer interpolation (ILIP) and the interlayer base mode (ILBM) method, and enable ET and TT savings of up to 69.3% and 83.6%, respectively. The algorithms of the second category are based on full-search SVC spatial scalability. They utilize two methods, namely, full interpolation (FIP) and the full-base mode (FBM) method, and enable ET and TT savings of up to 55.3% and 76.6%, respectively.

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Section: Experiments and Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%