{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:28:00Z","timestamp":1740202080570,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"abstract":"<jats:p>The newest standard of video coding, the high efficiency video coding (HEVC) achieves significantly better coding efficiency than all existing video coding standards. HEVC adopts the quadtree-structured coding unit (CU) to improve the coding efficiency. Each CU node in quadtree will be traversed by depth first search process to find the best coding tree unit (CTU) partition. Although this quadtree search process can obtain the best CTU partition, it requires a very high computational complexity, especially the motion estimation (ME) process in interframe coding. To alleviate the encoder computation load in interframe coding, a fast CU depth range decision (FCUDRD) method is proposed by reducing the depth search range. Based on the depth information correlation between temporal-spatial adjacent CTUs and the current CTU, some depths can be adaptively excluded from the depth search process in advance. The best depth of current CTU is determined by an intersection between temporal predicted depth ranges by 9 Gaussian weightings from encoded blocks and spatial predicted depth ranges by 4 best weightings from encoded blocks, separately. Experimental results show that the FCUDRDcan achieve time improving ratio (TIR) about 55.73% for RA and 65.77%for LD on average, respectively, as compared to the HM8.1 with insignificant loss of image quality.<\/jats:p>","DOI":"10.3233\/978-1-61499-484-8-1287","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:27:24Z","timestamp":1740133644000},"source":"Crossref","is-referenced-by-count":0,"title":["Fast Coding Unit Depth Decision Method for HEVC Encoders"],"prefix":"10.3233","author":[{"family":"Wang Chou-Chen","sequence":"additional","affiliation":[]},{"family":"Wang Hsiang-Chun","sequence":"additional","affiliation":[]},{"family":"Jhou Ming-Shum","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Intelligent Systems and Applications"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:21:49Z","timestamp":1740136909000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISSNISBN&issn=0922-6389&volume=274&spage=1287"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-484-8-1287","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2015]]}}}