{"title":"高效视频编码的多层复杂性分配与动态控制方案","authors":"Jiunn-Tsair Fang, Ju-Kai Chen","doi":"10.1007/s11554-024-01452-6","DOIUrl":null,"url":null,"abstract":"<p>High-efficiency video coding (HEVC) has significantly improved coding efficiency; however, its quadtree (QT) structures for coding units (CU) substantially raise the overall coding complexity. This study introduces a novel complexity control scheme aimed at enhancing HEVC encoding efficiency. The proposed scheme operates across multiple layers, encompassing the group of pictures (GOP) layer, frame layer, and coding-tree unit (CTU) layer. Each coding layer is assigned a limited coding complexity based on the remaining coding time. Particularly noteworthy is the dynamic scheme implemented to activate the complexity control method. To further expedite encoding, an efficient algorithm is developed for the CTU layer. Experimental results indicate that the 0.46% and 0.98% increases in BD-rate under the target complexity are reduced to 80% and 60% of the complexity constraint, respectively. The rate-distortion performance surpasses existing state-of-the-art complexity control methods, demonstrating the effectiveness of the proposed approach in enhancing HEVC encoding efficiency.</p>","PeriodicalId":51224,"journal":{"name":"Journal of Real-Time Image Processing","volume":"48 1","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multiple layers complexity allocation with dynamic control scheme for high-efficiency video coding\",\"authors\":\"Jiunn-Tsair Fang, Ju-Kai Chen\",\"doi\":\"10.1007/s11554-024-01452-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>High-efficiency video coding (HEVC) has significantly improved coding efficiency; however, its quadtree (QT) structures for coding units (CU) substantially raise the overall coding complexity. This study introduces a novel complexity control scheme aimed at enhancing HEVC encoding efficiency. The proposed scheme operates across multiple layers, encompassing the group of pictures (GOP) layer, frame layer, and coding-tree unit (CTU) layer. Each coding layer is assigned a limited coding complexity based on the remaining coding time. Particularly noteworthy is the dynamic scheme implemented to activate the complexity control method. To further expedite encoding, an efficient algorithm is developed for the CTU layer. Experimental results indicate that the 0.46% and 0.98% increases in BD-rate under the target complexity are reduced to 80% and 60% of the complexity constraint, respectively. The rate-distortion performance surpasses existing state-of-the-art complexity control methods, demonstrating the effectiveness of the proposed approach in enhancing HEVC encoding efficiency.</p>\",\"PeriodicalId\":51224,\"journal\":{\"name\":\"Journal of Real-Time Image Processing\",\"volume\":\"48 1\",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Real-Time Image Processing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s11554-024-01452-6\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Real-Time Image Processing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s11554-024-01452-6","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Multiple layers complexity allocation with dynamic control scheme for high-efficiency video coding
High-efficiency video coding (HEVC) has significantly improved coding efficiency; however, its quadtree (QT) structures for coding units (CU) substantially raise the overall coding complexity. This study introduces a novel complexity control scheme aimed at enhancing HEVC encoding efficiency. The proposed scheme operates across multiple layers, encompassing the group of pictures (GOP) layer, frame layer, and coding-tree unit (CTU) layer. Each coding layer is assigned a limited coding complexity based on the remaining coding time. Particularly noteworthy is the dynamic scheme implemented to activate the complexity control method. To further expedite encoding, an efficient algorithm is developed for the CTU layer. Experimental results indicate that the 0.46% and 0.98% increases in BD-rate under the target complexity are reduced to 80% and 60% of the complexity constraint, respectively. The rate-distortion performance surpasses existing state-of-the-art complexity control methods, demonstrating the effectiveness of the proposed approach in enhancing HEVC encoding efficiency.
期刊介绍:
Due to rapid advancements in integrated circuit technology, the rich theoretical results that have been developed by the image and video processing research community are now being increasingly applied in practical systems to solve real-world image and video processing problems. Such systems involve constraints placed not only on their size, cost, and power consumption, but also on the timeliness of the image data processed.
Examples of such systems are mobile phones, digital still/video/cell-phone cameras, portable media players, personal digital assistants, high-definition television, video surveillance systems, industrial visual inspection systems, medical imaging devices, vision-guided autonomous robots, spectral imaging systems, and many other real-time embedded systems. In these real-time systems, strict timing requirements demand that results are available within a certain interval of time as imposed by the application.
It is often the case that an image processing algorithm is developed and proven theoretically sound, presumably with a specific application in mind, but its practical applications and the detailed steps, methodology, and trade-off analysis required to achieve its real-time performance are not fully explored, leaving these critical and usually non-trivial issues for those wishing to employ the algorithm in a real-time system.
The Journal of Real-Time Image Processing is intended to bridge the gap between the theory and practice of image processing, serving the greater community of researchers, practicing engineers, and industrial professionals who deal with designing, implementing or utilizing image processing systems which must satisfy real-time design constraints.