{"created":"2024-11-22T07:32:16.302080+00:00","id":2008648,"links":{},"metadata":{"_buckets":{"deposit":"a2762cff-5dd7-4e97-b233-235435a92fd7"},"_deposit":{"created_by":7,"id":"2008648","owners":[7],"pid":{"revision_id":0,"type":"depid","value":"2008648"},"status":"published"},"_oai":{"id":"oai:tokushima-u.repo.nii.ac.jp:02008648","sets":["1713853213384:1713853295607"]},"author_link":["976","1231"],"control_number":"2008648","item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2019-04-24","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"8","bibliographicPageStart":"1927","bibliographicVolumeNumber":"19","bibliographic_titles":[{"bibliographic_title":"Sensors","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Real-time video streaming over vehicular ad-hoc networks (VANETs) has been considered as a critical challenge for road safety applications. The purpose of this paper is to reduce the computation complexity of high efficiency video coding (HEVC) encoder for VANETs. Based on a novel spatiotemporal neighborhood set, firstly the coding tree unit depth decision algorithm is presented by controlling the depth search range. Secondly, a Bayesian classifier is used for the prediction unit decision for inter-prediction, and prior probability value is calculated by Gibbs Random Field model. Simulation results show that the overall algorithm can significantly reduce encoding time with a reasonably low loss in encoding efficiency. Compared to HEVC reference software HM16.0, the encoding time is reduced by up to 63.96%, while the Bjontegaard delta bit-rate is increased by only 0.76–0.80% on average. Moreover, the proposed HEVC encoder is low-complexity and hardware-friendly for video codecs that reside on mobile vehicles for VANETs.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"MDPI","subitem_publisher_language":"en"}]},"item_10001_rights_15":{"attribute_name":"権利情報","attribute_value_mlt":[{"subitem_rights":"This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license 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