H. Aomori, K. Kawakami, T. Otake, N. Takahashi, M. Yamauchi, M. Tanaka
{"title":"基于提升方案的高动态范围图像无损编码,利用离散时间细胞神经网络的非线性插值效应","authors":"H. Aomori, K. Kawakami, T. Otake, N. Takahashi, M. Yamauchi, M. Tanaka","doi":"10.1109/IJCNN.2005.1556132","DOIUrl":null,"url":null,"abstract":"The lifting scheme is a flexible method for the construction of linear and nonlinear wavelet transforms. In this paper, we propose a novel lossless high dynamic range (HDR) image coding method based on the lifting scheme using discrete-time cellular neural networks (DT-CNNs). In our proposed method, the image is interpolated by using the nonlinear interpolative dynamics of DT-CNN. Because the output function of DT-CNN works as a multi-level quantization function, our method adapts for the prediction of HDR image, and composes the integer lifting scheme for lossless coding. Moreover, our method makes good use of the nonlinear interpolative dynamics by A-template compared with conventional CNN image coding methods using only B-template. The experimental results show a better coding performance compared with the conventional lifting method using linear filters.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"16 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Lossless high dynamic range image coding based on lifting scheme using nonlinear interpolative effect of discrete-time cellular neural networks\",\"authors\":\"H. Aomori, K. Kawakami, T. Otake, N. Takahashi, M. Yamauchi, M. Tanaka\",\"doi\":\"10.1109/IJCNN.2005.1556132\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The lifting scheme is a flexible method for the construction of linear and nonlinear wavelet transforms. In this paper, we propose a novel lossless high dynamic range (HDR) image coding method based on the lifting scheme using discrete-time cellular neural networks (DT-CNNs). In our proposed method, the image is interpolated by using the nonlinear interpolative dynamics of DT-CNN. Because the output function of DT-CNN works as a multi-level quantization function, our method adapts for the prediction of HDR image, and composes the integer lifting scheme for lossless coding. Moreover, our method makes good use of the nonlinear interpolative dynamics by A-template compared with conventional CNN image coding methods using only B-template. The experimental results show a better coding performance compared with the conventional lifting method using linear filters.\",\"PeriodicalId\":365690,\"journal\":{\"name\":\"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.\",\"volume\":\"16 5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.2005.1556132\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.2005.1556132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lossless high dynamic range image coding based on lifting scheme using nonlinear interpolative effect of discrete-time cellular neural networks
The lifting scheme is a flexible method for the construction of linear and nonlinear wavelet transforms. In this paper, we propose a novel lossless high dynamic range (HDR) image coding method based on the lifting scheme using discrete-time cellular neural networks (DT-CNNs). In our proposed method, the image is interpolated by using the nonlinear interpolative dynamics of DT-CNN. Because the output function of DT-CNN works as a multi-level quantization function, our method adapts for the prediction of HDR image, and composes the integer lifting scheme for lossless coding. Moreover, our method makes good use of the nonlinear interpolative dynamics by A-template compared with conventional CNN image coding methods using only B-template. The experimental results show a better coding performance compared with the conventional lifting method using linear filters.