计算机技术、通信技术 |
|
|
|
|
稀疏分解和图拉普拉斯正则化的图像前景背景分割方法 |
谭婷芳1( ),蔡万源1,蒋俊正1,2,3,*( ) |
1. 桂林电子科技大学 信息与通信学院,广西壮族自治区 桂林 541004 2. 桂林电子科技大学 卫星导航定位与位置服务国家地方联合工程研究中心,广西壮族自治区 桂林 541004 3. 西安电子科技大学 杭州研究院,浙江 杭州 311231 |
|
Image foreground-background segmentation method based on sparse decomposition and graph Laplacian regularization |
Tingfang TAN1( ),Wanyuan CAI1,Junzheng JIANG1,2,3,*( ) |
1. School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China 2. State and Local Joint Engineering Research Center for Satellite Navigation and Location Service, Guilin University of Electronic Technology, Guilin 541004, China 3. Hangzhou Institute of Technology, Xidian University, Hangzhou 311231, China |
1 |
MUKHERJEE D, CHRYSAFIS C, SAID A. JPEG2000-matched MRC compression of compound documents [C]// Proceedings. International Conference on Image Processing . Rochester: IEEE, 2002.
|
2 |
WANG G, LI W, ZULUAGA M A, et al Interactive medical image segmentation using deep learning with image-specific fine tuning[J]. IEEE Transactions on Medical Imaging, 2018, 37 (7): 1562- 1573
doi: 10.1109/TMI.2018.2791721
|
3 |
YIN X C, ZUO Z Y, TIAN S, et al Text detection, tracking and recognition in video: a comprehensive survey[J]. IEEE Transactions on Image Processing, 2016, 25 (6): 2752- 2773
doi: 10.1109/TIP.2016.2554321
|
4 |
LIN T, HAO P Compound image compression for real-time computer screen image transmission[J]. IEEE Transactions on Image Processing, 2005, 14 (8): 993- 1005
doi: 10.1109/TIP.2005.849776
|
5 |
BOTTOU L, HAFFNER P, HOWARD P G, et al High quality document image compression with "DjVu"[J]. Journal of Electronic Imaging, 1998, 7 (3): 410- 425
doi: 10.1117/1.482609
|
6 |
MINAEE S, WANG Y. Screen content image segmentation using least absolute deviation fitting [C]// IEEE International Conference on Image Processing . Quebec City: IEEE, 2015: 3295-3299.
|
7 |
MINAEE S, WANG Y. Screen content image segmentation using sparse decomposition and total variation minimization [C]// IEEE International Conference on Image Processing . Phoenix: IEEE, 2016: 3882-3886.
|
8 |
MINAEE S, WANG Y An ADMM approach to masked signal decomposition using subspace representation[J]. IEEE Transactions on Image Processing, 2019, 28 (7): 3192- 3204
doi: 10.1109/TIP.2019.2894966
|
9 |
HU W, PANG J, LIU X, et al Graph signal processing for geometric data and beyond: theory and applications[J]. IEEE Transactions on Multimedia, 2021, 24: 3961- 3977
|
10 |
ORTEGA A, FROSSARD P, KOVAČEVIĆ J, et al Graph signal processing: overview, challenges, and applications[J]. Proceedings of the IEEE, 2018, 106 (5): 808- 828
doi: 10.1109/JPROC.2018.2820126
|
11 |
SHUMAN D I, NARANG S K, FROSSARD P, et al The emerging field of signal processing on graphs: extending high-dimensional data analysis to networks and other irregular domains[J]. IEEE Signal Processing Magazine, 2013, 30 (3): 83- 98
doi: 10.1109/MSP.2012.2235192
|
12 |
ABIKO K, URUMA K, SUGAWARA M, et al. Image segmentation based graph-cut approach to fast color image coding via graph Fourier transform [C]// IEEE Visual Communications and Image Processing . Sydney: IEEE, 2019: 457-460.
|
13 |
BOGACH I V, LUPIAK D D, IVANOV Y Y, et al. Analysis and experimental research of modifications of the image segmentation method using graph theory [C]// International Siberian Conference on Control and Communications . Tomsk: IEEE, 2019: 490-493.
|
14 |
HU W, CHEUNG G, ORTEGA A, et al Multiresolution graph Fourier transform for compression of piecewise smooth images[J]. IEEE Transactions on Image Processing, 2015, 24 (1): 419- 433
doi: 10.1109/TIP.2014.2378055
|
15 |
PANG J, CHEUNG G Graph Laplacian regularization for image denoising: analysis in the continuous domain[J]. IEEE Transactions on Image Processing, 2017, 26 (4): 1770- 1785
doi: 10.1109/TIP.2017.2651400
|
16 |
刘娜, 李伟, 陶然 图信号处理在高光谱图像处理领域的典型应用[J]. 电子与信息学报, 2023, 45 (5): 1529- 1540 LIU Na, LI Wei, TAO Ran Typical application of graph signal processing in hyperspectral image processing[J]. Journal of Electronics and Information Technology, 2023, 45 (5): 1529- 1540
|
17 |
DONG X, THANOU D, TONI L, et al Graph signal processing for machine learning: a review and new perspectives[J]. IEEE Signal Processing Magazine, 2020, 37 (6): 117- 127
doi: 10.1109/MSP.2020.3014591
|
18 |
CAI W, JIANG J, OUYANG S Hyperspectral image denoising using adaptive weight graph total variation regularization and low-rank matrix recovery[J]. IEEE Geoscience and Remote Sensing Letters, 2021, 19: 1- 5
|
19 |
ACHANTA R, HEMAMI S, ESTRADA F, et al. Frequency-tuned salient region detection [C]// IEEE Conference on Computer Vision and Pattern Recognition . Miami: IEEE, 2009: 1597-1604.
|
20 |
MIN X, MA K, GU K, et al Unified blind quality assessment of compressed natural, graphic, and screen content images[J]. IEEE Transactions on Image Processing, 2017, 26 (11): 5462- 5474
doi: 10.1109/TIP.2017.2735192
|
21 |
JIANG J, FENG H, TAY D B, et al Theory and design of joint time-vertex nonsubsampled filter banks[J]. IEEE Transactions on Signal Processing, 2021, 69: 1968- 1982
doi: 10.1109/TSP.2021.3064984
|
22 |
TAY D B, JIANG J Time-varying graph signal denoising via median filters[J]. IEEE Transactions on Circuits and Systems II: Express Briefs, 2021, 68 (3): 1053- 1057
|
23 |
SANDRYHAILA A, MOURA J M F Big data analysis with signal processing on graphs: representation and processing of massive data sets with irregular structure[J]. IEEE Signal Processing Magazine, 2014, 31 (5): 80- 90
doi: 10.1109/MSP.2014.2329213
|
24 |
THANOU D, FROSSARD P. Multi-graph learning of spectral graph dictionaries [C]// IEEE International Conference on Acoustics, Speech and Signal Processing . South Brisbane: IEEE, 2015: 3397-3401.
|
25 |
QIU K, MAO X, SHEN X, et al Time-varying graph signal reconstruction[J]. IEEE Journal of Selected Topics in Signal Processing, 2017, 11 (6): 870- 883
doi: 10.1109/JSTSP.2017.2726969
|
26 |
QI W, GUO S, HU W Generic reversible visible watermarking via regularized graph Fourier transform coding[J]. IEEE Transactions on Image Processing, 2021, 31: 691- 705
|
27 |
CHEUNG G, MAGLI E, TANAKA Y, et al Graph spectral image processing[J]. Proceedings of the IEEE, 2018, 106 (5): 907- 930
doi: 10.1109/JPROC.2018.2799702
|
28 |
LIU M, WEI Y. Image denoising using graph-based frequency domain low-pass filtering [C]// IEEE 4th International Conference on Image, Vision and Computing. Xiamen: IEEE, 2019: 118-122.
|
29 |
KE G Y, PAN Y, YIN J, et al Optimizing evaluation metrics for multitask learning via the alternating direction method of multipliers[J]. IEEE Transactions on Cybernetics, 2017, 48 (3): 993- 1006
|
30 |
孙菲, 厉小润, 赵辽英, 等 基于FrFT变换和全变分正则化的异常检测算法[J]. 浙江大学学报:工学版, 2022, 56 (7): 1276- 1284 SUN Fei, LI Xiaorun, ZHAO Liaoying, et al Anomaly detection algorithm based on FrFT transform and total variation regularization[J]. Journal of Zhejiang University: Engineering Science, 2022, 56 (7): 1276- 1284
|
31 |
BOYD S, PARIKH N, CHU E, et al Distributed optimization and statistical learning via the alternating direction method of multipliers[J]. Foundations and Trends in Machine Learning, 2011, 3 (1): 1- 122
|
32 |
ZHANG Y, CHANDLER D M, MOU X Quality assessment of screen content images via convolutional-neural-network-based synthetic/natural segmentation[J]. IEEE Transactions on Image Processing, 2018, 27 (10): 5113- 5128
doi: 10.1109/TIP.2018.2851390
|
33 |
ARAVKIN A, BECKER S, CEVHER V, et al. A variational approach to stable principal component pursuit [EB/OL]. [2014-06-04]. https://arxiv.org/abs/1406.1089.
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|