基于自适应下采样和超分重建的图像压缩框架
[1] BRUCKSTEIN A,ELAD M,KIMMEL R. Down-scaling for better transform compression[J]. IEEE Transactions on Image
Processing, 2003,12(9):1132-1144.
BRUCKSTEIN A,ELAD M,KIMMEL R. Down-scaling for better transform compression[J]. IEEE Transactions on Image Processing, 2003,12(9):1132-1144.
BRUCKSTEIN A,ELAD M,KIMMEL R. Down-scaling for better transform compression[J]. IEEE Transactions on Image Processing, 2003,12(9):1132-1144.
[2] ZHANG Jian,XIONG Ruiqin,ZHAO Chen,et al. CONCOLOR: constrained non-convex low-rank model for image deblocking[J]. IEEE Transactions on Image Processing, 2016,25(3):1246-1259.
ZHANG Jian,XIONG Ruiqin,ZHAO Chen,et al. CONCOLOR: constrained non-convex low-rank model for image deblocking[J]. IEEE Transactions on Image Processing, 2016,25(3):1246-1259.
IEEE Transactions on Image Processing, 2016,25(3):1246-1259.
ZHANG Jian,XIONG Ruiqin,ZHAO Chen,et al. CONCOLOR: constrained non-convex low-rank model for image deblocking[J].
[3] Processing, 2006,15(9):2513-2521.
LIN Weisi,LI Dong. Adaptive downsampling to improve image compression at low bit rates[J]. IEEE Transactions on Image
LIN Weisi,LI Dong. Adaptive downsampling to improve image compression at low bit rates[J]. IEEE Transactions on Image Processing, 2006,15(9):2513-2521.
LIN Weisi,LI Dong. Adaptive downsampling to improve image compression at low bit rates[J]. IEEE Transactions on Image Processing, 2006,15(9):2513-2521.
[4] CHEN Honggang,HE Xiaohai,MA Minglang,et al. Low bit rates image compression via adaptive block downsampling and super resolution[J]. Journal of Electronic Imaging, 2016,25(1):013004.
CHEN Honggang,HE Xiaohai,MA Minglang,et al. Low bit rates image compression via adaptive block downsampling and super resolution[J]. Journal of Electronic Imaging, 2016,25(1):013004.
super resolution[J]. Journal of Electronic Imaging, 2016,25(1):013004.
CHEN Honggang,HE Xiaohai,MA Minglang,et al. Low bit rates image compression via adaptive block downsampling and
[5] LI Yang,SUN Xiaoyan,XIONG Hongkai,et al. Incorporating primal sketch based learning into low bit-rate image compression[C]// IEEE International Conference on Image Processing. San Antonio:IEEE, 2007:173-176.
LI Yang,SUN Xiaoyan,XIONG Hongkai,et al. Incorporating primal sketch based learning into low bit-rate image compression[C]// IEEE International Conference on Image Processing. San Antonio:IEEE, 2007:173-176.
LI Yang,SUN Xiaoyan,XIONG Hongkai,et al. Incorporating primal sketch based learning into low bit-rate image compression[C]//
IEEE International Conference on Image Processing. San Antonio:IEEE, 2007:173-176.
[6] DONG C,LOY C C,HE K M,et al. Learning a deep convolutional network for image super-resolution[C]// European Conference on Computer Vision. Berlin:Springer Verlag, 2014:184-199.
DONG C,LOY C C,HE K M,et al. Learning a deep convolutional network for image super-resolution[C]// European Conference on
DONG C,LOY C C,HE K M,et al. Learning a deep convolutional network for image super-resolution[C]// European Conference on Computer Vision. Berlin:Springer Verlag, 2014:184-199.
Computer Vision. Berlin:Springer Verlag, 2014:184-199.
[7] DONG C,LOY C C,TANG X. Accelerating the super-resolution convolutional neural network[C]// European Conference on Computer Vision. Amsterdam:Springer, 2016:391-407.
DONG C,LOY C C,TANG X. Accelerating the super-resolution convolutional neural network[C]// European Conference on
DONG C,LOY C C,TANG X. Accelerating the super-resolution convolutional neural network[C]// European Conference on Computer Vision. Amsterdam:Springer, 2016:391-407.
Computer Vision. Amsterdam:Springer, 2016:391-407.
李素梅,雷国庆,范如. 基于卷积神经网络的深度图超分辨力重建[J]. 光学学报, 2017,37(12):1210002. (LI Sumei,
[9] 徐冉,张俊格,黄凯奇. 利用双通道卷积神经网络的图像超分辨力算法[J]. 中国图象图形学报, 2016,21(5):556-564.
徐冉,张俊格,黄凯奇. 利用双通道卷积神经网络的图像超分辨力算法[J]. 中国图象图形学报, 2016,21(5):556-564.(XU Ran,ZHANG Junge,HUANG Kaiqi. Image super-resolution using two-channel convolutional neural networks[J]. Journal ofImage and Graphics, 2016,21(5):556-564.)
徐冉,张俊格,黄凯奇. 利用双通道卷积神经网络的图像超分辨力算法[J]. 中国图象图形学报, 2016,21(5):556-564.(XU Ran,ZHANG Junge,HUANG Kaiqi. Image super-resolution using two-channel convolutional neural networks[J]. Journal ofImage and Graphics, 2016,21(5):556-564.)
(XU Ran,ZHANG Junge,HUANG Kaiqi. Image super-resolution using two-channel convolutional neural networks[J]. Journal of
Image and Graphics, 2016,21(5):556-564.)
[10] 胡长胜,詹曙,吴从中. 基于深度特征学习的图像超分辨力重建[J]. 自动化学报, 2017,43(5):814-821. (HU Changsheng,ZHAN Shu,WU Congzhong. Image super-resolution based on deep learning features[J]. Acta Automatica Sinica, 2017,43(5):814-821.)
胡长胜,詹曙,吴从中. 基于深度特征学习的图像超分辨力重建[J]. 自动化学报, 2017,43(5):814-821. (HU Changsheng,
胡长胜,詹曙,吴从中. 基于深度特征学习的图像超分辨力重建[J]. 自动化学报, 2017,43(5):814-821. (HU Changsheng,ZHAN Shu,WU Congzhong. Image super-resolution based on deep learning features[J]. Acta Automatica Sinica, 2017,43(5):814-821.)
43(5):814-821.)
ZHAN Shu,WU Congzhong. Image super-resolution based on deep learning features[J]. Acta Automatica Sinica, 2017,
[11] KIM J,LEE J K,LEE K M. Accurate image super-resolution using very deep convolutional networks[C]//Proceedings of the
IEEE Conference on Computer Vision and Pattern Recognition. Washington,USA:IEEE Computer Society, 2016:1646-
KIM J,LEE J K,LEE K M. Accurate image super-resolution using very deep convolutional networks[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Washington,USA:IEEE Computer Society, 2016:1646-1654.
KIM J,LEE J K,LEE K M. Accurate image super-resolution using very deep convolutional networks[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Washington,USA:IEEE Computer Society, 2016:1646-1654.
1654.
[12] CHEN H,HE X,REN C,et al. CISRDCNN:super-resolution of compressed images using deep convolutional neural networks[J].Neurocomputing, 2018(285):204-219.
CHEN H,HE X,REN C,et al. CISRDCNN:super-resolution of compressed images using deep convolutional neural networks[J].Neurocomputing, 2018(285):204-219.
[13] ZEYDE R,ELAD M,PROTTER M. On single image scale-up using sparse-representations[C]// International Conference on Curves and Surfaces. Avignon,France:[s.n.], 2010:711-730.
ZEYDE R,ELAD M,PROTTER M. On single image scale-up using sparse-representations[C]// International Conference on Curves and Surfaces. Avignon,France:[s.n.], 2010:711-730.
[14] HUANG J B,SINGH A,AHUJA N. Single image super-resolution from transformed self-exemplars[C]// IEEE Conference on Computer Vision and Pattern Recognition. Boston,USA:IEEE Computer Society, 2015:5197-5206.
HUANG J B,SINGH A,AHUJA N. Single image super-resolution from transformed self-exemplars[C]// IEEE Conference on Computer Vision and Pattern Recognition. Boston,USA:IEEE Computer Society, 2015:5197-5206.
[15] WEBER A G. The USC-SIPI image database version 5[J]. USC-SIPI Report, 1997(315):1-24.
WEBER A G. The USC-SIPI image database version 5[J]. USC-SIPI Report, 1997(315):1-24.
[16] KRIZHEVSKY A,SUTSKEVER I,HINTON G E. Image net classification with deep convolutional neural networks[J]. Advances in Neural Information Processing Systems, 2012(1):1097-1105.
KRIZHEVSKY A,SUTSKEVER I,HINTON G E. Image net classification with deep convolutional neural networks[J]. Advances in Neural Information Processing Systems, 2012(1):1097-1105.
[17] DABOV K,FOI A,EGIAZARIAN K. Image denoising with block-matchin g and 3D filter i n g[J]. Proceedings of Society of Photo-Optical Instrumentation Engineers, 2006(6064):354-365.
DABOV K,FOI A,EGIAZARIAN K. Image denoising with block-matchin g and 3D filter i n g[J]. Proceedings of Society of Photo-Optical Instrumentation Engineers, 2006(6064):354-365.
张达明, 何小海, 任超, 吴晓红, 李兴龙, 范梦. 基于自适应下采样和超分重建的图像压缩框架[J]. 太赫兹科学与电子信息学报, 2020, 18(2): 298. ZHANG Daming, HE Xiaohai, REN Chao, WU Xiaohong, LI Xinglong, FAN Meng. Image compression framework based on adaptive sub-sampling and super-resolution reconstruction[J]. Journal of terahertz science and electronic information technology, 2020, 18(2): 298.