计算机技术 |
|
|
|
|
视觉特征深度融合的图像质量评价 |
丰明坤(),施祥 |
浙江科技学院 信息与电子工程学院,浙江 杭州 310023 |
|
Image quality assessment with deep pooling of visual feature |
Ming-kun FENG(),Xiang SHI |
School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China |
1 |
GUO Y C, HAO Y T, YU M Image retargeting quality assessment based on content deformation measurement[J]. Signal Processing: Image Communication, 2018, 67 (6): 171- 181
|
2 |
CHEN Z B, LIN J X, LIAO N, et al Full reference quality assessment for image retargeting based on natural scene statistics modeling and bi-directional saliency similarity[J]. IEEE Transactions on Image Processing, 2017, 26 (11): 5138- 5148
doi: 10.1109/TIP.2017.2736422
|
3 |
ZHANG Y CH, KING N N, MA L, et al Objective quality assessment of image retargeting by incorporating fidelity measures and inconsistency detection[J]. IEEE Transactions on Image Processing, 2017, 26 (11): 5980- 5993
|
4 |
ZHANG Y B, LIN W S, LI Q H, et al Multiple-level feature-based measure for retargeted image quality[J]. IEEE Transactions on Image Processing, 2018, 27 (1): 451- 463
doi: 10.1109/TIP.2017.2761556
|
5 |
丰明坤, 王中鹏, 叶绿 视觉稀疏化多通道多特征自适应的图像评价[J]. 仪器仪表学报, 2016, 37 (3): 667- 674 FENG Ming-kun, WANG ZHong-peng, YE Lv Image quality assessment based on adaptive sparse visual multi-channel and multi-feature pooling[J]. Chinese Journal of Scientific Instrument, 2016, 37 (3): 667- 674
doi: 10.3969/j.issn.0254-3087.2016.03.025
|
6 |
BAMPIS C G, GUPTA P, SOUNDARARAJAN R, et al SpEED-QA: patial efficient entropic differencing for image and video quality[J]. IEEE Signal Processing Letters, 2017, 24 (9): 1333- 1337
doi: 10.1109/LSP.2017.2726542
|
7 |
NI ZH K, MA L, ZENG H Q, et al Gradient direction for screen content image quality assessment[J]. IEEE Signal Processing Letters, 2016, 23 (10): 1394- 1398
doi: 10.1109/LSP.2016.2599294
|
8 |
KIM J, ZENG H, GHADIYARAM D, et al Deep convolutional neural models for picture-quality prediction: challenges and solutions to data-driven image quality assessment[J]. IEEE Signal Processing Magazine, 2017, 34 (6): 130- 141
doi: 10.1109/MSP.2017.2736018
|
9 |
GHADIYARAM D, BOVIK A. C Massive online crowdsourced study of subjective and objective picture quality[J]. IEEE Transactions on Image Process, 2016, 25 (1): 372- 387
doi: 10.1109/TIP.2015.2500021
|
10 |
LARSON E C, CHANDLER D M Most apparent distortion: full-reference image quality assessment and the role of strategy[J]. Journal of Electronic Imaging, 2010, 19 (1): 011006-1- 011006-21
|
11 |
ZHANG L, ZHANG L, MOU X Q, et al FSIM: a feature similarity index for image quality assessment[J]. IEEE Transactions on Image Processing, 2011, 20 (8): 2378- 2386
doi: 10.1109/TIP.2011.2109730
|
12 |
ZHANG L, SHEN Y LI H Y VSI: a visual saliency-induced index for perceptual image quality assessment[J]. IEEE Transactions on Image Processing, 2014, 23 (10): 4270- 4281
doi: 10.1109/TIP.2014.2346028
|
13 |
DING Y, WANG SH Z, ZHANG D Full-reference image quality assessment using statistical local correlation[J]. Electronics Letters, 2014, 50 (2): 79- 81
doi: 10.1049/el.2013.3365
|
14 |
WU J J, LIN W S, SHI G M Perceptual quality metric with internal generative mechanism[J]. IEEE Transactions on Image Processing, 2013, 22 (1): 43- 54
doi: 10.1109/TIP.2012.2214048
|
15 |
丰明坤, 赵生妹, 邢超 基于视觉显著失真度的图像质量自适应评价方法[J]. 电子与信息学报, 2015, 37 (9): 2062- 2068 FENG Ming-kun, ZHAO SHeng-mei, XING CHao Image quality self-adaptive assessment based on visual salience distortion[J]. Journal of Electronics & Information Technology, 2015, 37 (9): 2062- 2068
|
16 |
丰明坤, 赵生妹, 施祥 视觉多通道梯度与低阶矩自适应图像评价[J]. 仪器仪表学报, 2015, 36 (11): 2531- 2537 FENG Ming-kun, ZHAO SHeng-mei, SHI Xiang Adaptive image quality assessment based on visual multi-channel gradient and low order moment[J]. Chinese Journal of Scientific Instrument, 2015, 36 (11): 2531- 2537
doi: 10.3969/j.issn.0254-3087.2015.11.017
|
17 |
WANG ZH, BOVIK A C, SHEIKH H R, et al Image quality assessment: from error visibility to structural similarity[J]. IEEE Transactions on Image Processing, 2004, 13 (4): 600- 612
doi: 10.1109/TIP.2003.819861
|
18 |
WANG ZH, LU L G, BOVIK A C Foveation scalable video coding with automatic fixation selection[J]. IEEE Transactions on Image Processing, 2003, 12 (2): 243- 254
doi: 10.1109/TIP.2003.809015
|
19 |
LIU A M, LIN W S, NARWARIA M Image quality assessment based on gradient similarity[J]. IEEE Transaction on Image Processing, 2012, 21 (4): 1500- 1512
doi: 10.1109/TIP.2011.2175935
|
20 |
GAO X B, LU W, TAO D CH, et al Image quality assessment based on multiscale geometric analysis[J]. IEEE Transactions on Image Processing, 2009, 18 (7): 1409- 1423
doi: 10.1109/TIP.2009.2018014
|
21 |
林志洁, 丰明坤 深度视觉特征与策略互补融合的图像质量评价[J]. 模式识别与人工智能, 2017, 30 (8): 682- 691 LIN ZHi-jie, FENG Ming-kun Image quality assessment based on complementary pooling of deeply visual feature and strategy[J]. Pattern Recognition and Artificial Intelligence, 2017, 30 (8): 682- 691
|
22 |
SHNAYDERMAN A, GUSEV A, ESKICIOGLU A M An SVD-based grayscale image quality measure for local and global assessment[J]. IEEE Transactions on Image Processing, 2006, 15 (2): 422- 429
doi: 10.1109/TIP.2005.860605
|
23 |
HU A ZH, ZHANG R YIN D, et al Image quality assessment using an SVD-based structural projection[J]. Signal Processing: Image Communication, 2014, 29 (3): 293- 302
doi: 10.1016/j.image.2014.01.007
|
24 |
WANG ZH, SIMONCELLI E P, BOVIK A C. Multi-scale structural similarity for image quality assessment [C]// Proceedings of the 37th IEEE Asilomar Conference on Signals, Systems and Computers. Pacific Grove: IEEE, 2002(2): 1398–1402.
|
25 |
SHEIKH H R, BOVIK A C, VECIANA G D An information fidelity criterion for image quality assessment using natural scene statistics[J]. IEEE Transactions on Image Processing, 2005, 14 (12): 2117- 2128
doi: 10.1109/TIP.2005.859389
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|