Neighboring sample prediction coding for HEVC screen content coding

Yao Jen Chang, Ching Chieh Lin, Jih Sheng Tu, Chun Lung Lin, Chao Hsiung Hung, Pei Hsuan Tsai

Research output: Chapter in Book/Report/Conference proceedingConference contribution


High Efficiency Video Coding (HEVC) Screen Content Coding (SCC) is under standardizing for the screen-captured contents. Because many areas are composed of the texts and lines featuring non-smooth textures, the traditional intra prediction is not suitable for those areas. Therefore, this paper proposes a neighboring sample prediction coding (NSPC) for HEVC SCC, which represents the samples of the coding unit (CU) by the indexes of samples selected from the neighboring CUs. A unified sample selection scheme (USSS) based on a neighboring sample list is also proposed to determine the priority ordering of the selected neighboring samples. The index coding with a single sample index skipping method is also designed for coding the converted indexes. Different NSPC signaling methods are evaluated under the common test condition for HEVC SCC, and the results show that the NSPC improves the Bjontegaard-Delta bitrate saving of Screen Content Coding Test Model 2.0 up to 1.0%.

Original languageEnglish
Title of host publicationImage and Video Technology - 7th Pacific-Rim Symposium, PSIVT 2015, Revised Selected Papers
EditorsMariano Rivera, Brendan McCane, Xinguo Yu, Thomas Bräunl
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783319294506
Publication statusPublished - 2016 Jan 1
Event7th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2015 - Auckland, New Zealand
Duration: 2015 Nov 252015 Nov 27

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other7th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2015
Country/TerritoryNew Zealand

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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