Shuyuan Zhu, Zhiying He, Xiandong Meng, Guanghui Liu, B. Zeng
{"title":"基于压缩导向优化的多描述图像编码","authors":"Shuyuan Zhu, Zhiying He, Xiandong Meng, Guanghui Liu, B. Zeng","doi":"10.1109/PCS48520.2019.8954534","DOIUrl":null,"url":null,"abstract":"In this paper, we design a new multiple description coding scheme for image signals based on our proposed compression-guided optimization. Firstly, we propose a compression-constrained adaptive filtering method to produce two descriptions for the source image, where the proposed filtering algorithm works not only to guarantee a high-quality side decoding but also make a high-efficient central decoding. Secondly, we design a compression-dependent deblocking algorithm based on the transform coefficients which are decoded from both descriptions to improve the performance for the cental decoding. Experimental results demonstrate that our proposed method achieves impressive performance gains when it is applied to image signals.","PeriodicalId":237809,"journal":{"name":"2019 Picture Coding Symposium (PCS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multiple Description Image Coding Based on Compression-Guided Optimization\",\"authors\":\"Shuyuan Zhu, Zhiying He, Xiandong Meng, Guanghui Liu, B. Zeng\",\"doi\":\"10.1109/PCS48520.2019.8954534\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we design a new multiple description coding scheme for image signals based on our proposed compression-guided optimization. Firstly, we propose a compression-constrained adaptive filtering method to produce two descriptions for the source image, where the proposed filtering algorithm works not only to guarantee a high-quality side decoding but also make a high-efficient central decoding. Secondly, we design a compression-dependent deblocking algorithm based on the transform coefficients which are decoded from both descriptions to improve the performance for the cental decoding. Experimental results demonstrate that our proposed method achieves impressive performance gains when it is applied to image signals.\",\"PeriodicalId\":237809,\"journal\":{\"name\":\"2019 Picture Coding Symposium (PCS)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Picture Coding Symposium (PCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PCS48520.2019.8954534\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Picture Coding Symposium (PCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCS48520.2019.8954534","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiple Description Image Coding Based on Compression-Guided Optimization
In this paper, we design a new multiple description coding scheme for image signals based on our proposed compression-guided optimization. Firstly, we propose a compression-constrained adaptive filtering method to produce two descriptions for the source image, where the proposed filtering algorithm works not only to guarantee a high-quality side decoding but also make a high-efficient central decoding. Secondly, we design a compression-dependent deblocking algorithm based on the transform coefficients which are decoded from both descriptions to improve the performance for the cental decoding. Experimental results demonstrate that our proposed method achieves impressive performance gains when it is applied to image signals.