压缩视频超分辨率重建技术

徐忠强; 朱秀昌

doi:10.3724/SP.J.1146.2005.01199

压缩视频超分辨率重建技术

doi: 10.3724/SP.J.1146.2005.01199

基金项目:

江苏省自然科学基金(BK 2004151)资助课题

计量
- 文章访问数: 4125
- HTML全文浏览量: 108
- PDF下载量: 2476
- 被引次数: 0
出版历程
- 收稿日期: 2005-09-19
- 修回日期: 2006-04-03
- 刊出日期: 2007-02-19

Super-resolution Reconstruction Technology for Compressed Video

摘要

摘要: 超分辨率图像重建就是由低分辨率图像序列来估计高分辨率图像，而压缩视频的重建正成为当前研究的热点。本文首先分析了压缩视频重建的基础，建立了高、低分辨率图像间的关系，给出了量化噪声和运动矢量的模型；接着对目前最具有代表性的最大后验概率(MAP)算法、凸集投影(POCS)算法和迭代反向投影(IBP)算法进行了详细的阐述，并分别给出了实验结果；然后分析了运算的复杂度，介绍了几种实时化方法；最后针对目前存在的问题进行了展望，指出降质模型、运动估计、重建算法和实时应用将是今后研究的重点。
- 压缩视频;超分辨率;最大后验概率;凸集投影;迭代反向投影
Abstract: Super-Resolution (SR) reconstruction is to estimate High-Resolution (HR) images from Low-Resolution (LR) image sequence, which has been a great focus for compressed video. This paper firstly presents the base of SR reconstruction for compressed video by building the relationships between the HR and LR images and surveying the models of quantization noise and motion vector. Then, the typical algorithms such as MAP, POCS and IBP are described in detail with experimental results. The computation complexity and real-time approaches are also investigated. Finally, aiming at the drawbacks, the research rang of prospects are demonstrated through pointing out the focus on degradation mode, motion estimation, reconstruction algorithm and real-time implementations.

HTML全文

参考文献(1)

[1] Harris J L. Diffraction and resolving power[J].Journal of the Opt. Soc. of America.1964, 54 (7):931-936 [2] Tsai R and Huang T. Multi-frame image restoration and registration. Advances in Computer Vision and Image Processing, 1984, (1): 317-339. [3] Hunt B R. Super-resolution of imagery: Understanding the basis for recovery of spatial frequencies beyond the diffraction limit. Proceedings of Information, Decision and Control, Adelaide, Australia, 1999: 243-248. [4] Park S C, Park M K, and Kang M G. Super-resolution image reconstruction: A technical overview[J].IEEE Signal Processing Magazine.2003, 20(3):21-36 [5] Segall C A, Molina R, and Katsaggelos A K. High-Resolution Images from Low-resolution Compressed Video[J].IEEE Signal Processing Magazine.2003, 20(3):37-48 [6] Lam E Y and Goodman J W. A mathematical analysis of the DCT coefficient distributions for images[J].IEEE Trans. on Image Processing.2000, 9(10):1661-1666 [7] Robertson M A and Stevenson R L. DCT quantization noise in compressed images[J].IEEE Trans. on Circuits and Systems for Video Technology.2005, 15(1):27-38 [8] Chen D and Schultz R R. Extraction of high-resolution video stills from MPEG image sequences. IEEE Int. Conf. Image Processing, Chicago, IL, 1998, vol.2: 465-469. [9] Segall C A, Molina R, Katsaggelos A K, and Mateos J. Reconstruction of high-resolution image frames from a sequence of low-resolution and compressed observations. IEEE Int. Conf. Acoustics, Speech, Signal Processing, Orlando, Florida, 2002, vol.2: 1701-1704. [10] Park S C, Kang M G, Segall C A, and Katsaggelos A K. Spatially adaptive high-resolution image reconstruction of low-resolution DCT-based compressed images[J].IEEE Trans. on Image Processing.2004, 13(4):573-585 [11] Gunturk B K, Altunbasak Y, and Mersereau R M. Multi-frame resolution-enhancement methods for compressed video[J].IEEE Signal Processing Letters.2002, 9(6):170-174 [12] Mateos J, Katsaggelos A K, and Molina R. Simultaneous motion estimation and resolution enhancement of compressed low resolution video. IEEE Int. Conf. Image Processing, Vancouver, BC, 2000, vol.2: 653-656. [13] Segall C A, Katsaggelos A K, Molina R, and Mateos J. Bayesian resolution enhancement of compressed video[J].IEEE Trans. on Image Processing.2004, 13(7):898-911 [14] Gunturk B K, Antunbasak Y, and Mersereau R. Bayesian resolution-enhancement framework for transform-coded video. IEEE Int. Conf. Image Processing, Thessaloniki, Greece, 2001, vol.2: 41-44. [15] Gunturk B K, Altunbasak Y, and Mersereau R M. Super-resolution reconstruction of compressed video using transform-domain statistics[J].IEEE Trans. on Image Processing.2004, 13(1):33-43 [16] Segall C A, Katsaggelos A K, Molina R, and Mateos J. Super- Resolution from Compressed Video. In Super-Resolution Imaging. S. Chaudhuri, Ed. Norwell, MA: Kluwer, 2001: 211-242. [17] Stark H and Oskoui P. High-resolution image recovery from image-plane arrays, using convex projections[J].Journal of the Opt. Soc. of America (A.1989, 6 (11):1715-1726 [18] Patti A J, Sezan M I, and Tekalp A M. Super-resolution video reconstruction with arbitrary sampling lattices and nonzero aperture time[J].IEEE Trans. on Image Processing.1997, 6(8):1064-1076 [19] Paek H and Kim R. On the POCS-based post-processing technique to reduce the blocking artifacts in transform coded images. IEEE Trans. on Circuits and Systems for Video Technology, 1998, l8 (6): 358-367. [20] Altunbasak Y, Patti A J, and Mersereau R M. Super- resolution still and video reconstruction from MPEG coded video[J].IEEE Trans. on Circuits and System for Video Technology.2002, 12(4):217-226 [21] Irani M and Oskoui S. Improving resolution by image registration. Computer Vision, Graphics, and Image Processing, 1991, 53(5): 231-239 [22] Tom B C. Resolution enhancement of monochrome and color video using motion compensation[J].IEEE Trans. on Image Processing.2001, 10(2):278-287 [23] 张地, 杜明辉. POCS超分辨率图像重构的快速算法. 信息技术, 2004 , 28(7): 1-10. [24] Elad M and Feuer A. Super-resolution restoration of an image sequence: Adaptive filtering approach[J].IEEE Trans. on Image Processing.1999,8(3):387-395 [25] Elad M and Feuer A. Super-resolution reconstruction of continuous image sequences. IEEE Int. Conf. Image Processing, Kobe, Japan, Oct. 1999, vol. 3: 459-463. [26] Alam M S, Bognar J G, Hardie R C, and Yasuda B J. Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames[J].IEEE Trans. on Instrumentation and Measurement.2000, 49(5):915-923 [27] 韩玉兵, 陈小蔷,吴乐南. 一种视频序列的超分辨率重建算法. 电子学报, 2005, 33(1):126-130. [28] Callic G M, Llopis R P, and Sethuraman R. Low-cost implementation of a super-resolution algorithm for real-time video application. IEEE Int. Sym. Circuits and Systems, Kobe, Japan, 2005: 6130-6133. [29] Weiss Y and Adelson E H. A unified mixture framework for motion segmentation: incorporating spatial coherence and estimating the number of models. IEEE Computer Soc. Conf. Computer Vision and Pattern Recognition, San Francisco, California, 1996: 321-326. [30] Luettgen M R, Karl W C, and Willsky A S. Efficient multiscale regularization with applications to the computation of optical flow[J].IEEE Trans. on Image Processing.1994, 3(1):41-64 [31] 杜娟, 余英林, 谢胜利. 基于半像素运动信息的快速超分辨率图像重构算法. 华南理工大学学报(自然科学版), 2005, 33(5): 53-58. [32] Freeman W T, Jones T R, and Pasztor E C. Example-based super-resolution. IEEE Computer Graphics and Applications, 2002, 22 (2): 56-65. [33] Robertson M A and Stevenson R L. Temporal resolution enhancement in compressed video sequences. EURASIP Journal on Applied Signal Processing, 2001, 4: 230-238. [34] Shechtman E, Caspi Y, and Irani M. Space-time super- resolution[J].IEEE Trans. on Pattern Anal. Machine Intell.2005, 27(4):531-545 [35] 潘逢治, 张立明. 用神经网络恢复残差的图像超分辨率算法. 电子学报, 2004, 32(1): 162-165. [36] Borman S and Stevenson R L. Simultaneous multi-frame MAP super-resolution video enhancement using spatio- temporal priors. IEEE Int. Conf. Image Processing, Kobe, Japan, 1999, vol.3: 469-473. [37] Choi M G, Yang Y, and Galatsanos N P. Multichannel regularized recovery of compressed video sequences[J].IEEE Trans. on Circuits Syst. II: Analog and Digital Signal Processing.2001, 48(4):376-387 [38] Farsiu S, Robinson M D, Elad M, and Milanfar P. Fast and robust multiframe super resolution[J].IEEE Trans. on Image Processing.2004, 13(10):1327-1344 [39] Lee E and Kang M G. Regularized adaptive high-resolution image reconstruction considering inaccurate subpixel registration[J].IEEE Trans. on Image Processing.2003, 12(7):826-837 [40] 袁小华, 夏德深. 自适应正则有参超分辨率图像盲恢复.中国图象图形学报, 2004, 9(10): 1197-1203. [41] Sementilli P, Hunt B, and Nadar M. Analysis of the limit to super-resolution in incoherent imaging. Journal of the Opt. Soc. of America. 1993, 10(11): 2265-2276. [42] Baker S and Kanade T. Limits on super-resolution and how to break them[J].IEEE Trans. on Pattern Anal. Machine Intell.2002, 24(9):1167-1183 [43] Shahram M and Milanfar P. Imaging below the diffraction limit: A statistical analysis[J].IEEE Trans. on Image Processing.2004, 13(5):677-689

施引文献

资源附件(0)

访问统计