18.4.3.5 Range Data Super Resolution, Depth Super Resolution

Chapter Contents (Back)
Super Resolution. Depth Super Resolution. Depth Data. Range Data.

Yun, M.[Maojin], Liu, L.R.[Li-Ren], Sun, J.F.[Jian-Feng], Liu, D.[De'an],
Transverse or axial superresolution with radial birefringent filter,
JOSA-A(21), No. 10, October 2004, pp. 1869-1874.
WWW Link. 0501
BibRef

Yun, M.[Maojin], Liu, L.R.[Li-Ren], Sun, J.F.[Jian-Feng], Liu, D.[De'an],
Three-dimensional superresolution by three-zone complex pupil filters,
JOSA-A(22), No. 2, February 2005, pp. 272-277.
WWW Link. 0601
BibRef

Liu, H.T.[Hai-Tao], Mu, G.G.[Guo-Guang], Lin, L.[Lie], Fan, Z.W.[Zhong-Wei],
Optical superresolution of focused partially spatially coherent laser beams,
JOSA-A(23), No. 6, June 2006, pp. 1301-1310.
WWW Link. 0610
BibRef

Suresh, K.V.[Kaggere V.], Rajagopalan, A.N.[Ambasamudram N.],
Robust and computationally efficient superresolution algorithm,
JOSA-A(24), No. 4, April 2007, pp. 984-992.
WWW Link. 0801
BibRef

Rajagopalan, A.N.[Ambasamudram N.], Bhavsar, A.V.[Arnav V.], Wallhoff, F.[Frank], Rigoll, G.[Gerhard],
Resolution Enhancement of PMD Range Maps,
DAGM08(xx-yy).
Springer DOI 0806
BibRef

Bhavsar, A.V.[Arnav V.], Rajagopalan, A.N.[Ambasamudram N.],
Resolution enhancement for binocular stereo,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Prabhu, S.M.[Sahana M.], Rajagopalan, A.N.[Ambasamudram N.],
Matte Super-Resolution for Compositing,
DAGM10(422-431).
Springer DOI 1009
BibRef

Yu, Y.K.[Ying Kin], Wong, K.H.[Kin Hong], Chang, M.M.Y.[Michael Ming Yuen], Or, S.H.[Siu Hang],
Recursive Camera-Motion Estimation With the Trifocal Tensor,
SMC-B(36), No. 5, October 2006, pp. 1081-1090.
IEEE DOI 0609
BibRef

Yu, Y.K.[Ying Kin], Or, S.H.[Siu Hang], Wong, K.H.[Kin Hong], Chang, M.M.Y.[Michael Ming Yuen],
Accurate 3-D Motion Tracking with an Application to Super-Resolution,
ICPR06(III: 730-733).
IEEE DOI 0609
BibRef

Lee, M.[Moojae], Choi, J.J.[Jung-Ju], Wee, Y.[Youngcheul],
Improved Orthogonal Fractal Super-Resolution Using Range Adjustment and Domain Extension,
IEICE(E96-D), No. 8, August 2013, pp. 1890-1893.
WWW Link. 1308
BibRef

Chen, L.[Li], Tian, J.[Jing],
Depth image enlargement using an evolutionary approach,
SP:IC(28), No. 7, 2013, pp. 745-752.
Elsevier DOI 1307
BibRef
Earlier: A2, A1:
Depth image up-sampling using ant colony optimization,
ICPR12(3795-3798).
WWW Link. 1302
BibRef
And: A2, A1:
Bayesian image enlargement for mixed-resolution video,
ICPR12(3082-3085).
WWW Link. 1302
BibRef
Earlier: A2, A1:
Bayesian stereoscopic image resolution enhancement,
ICIP11(1505-1508).
IEEE DOI 1201
BibRef
Earlier: A2, A1:
Multi-focus image fusion using wavelet-domain statistics,
ICIP10(1205-1208).
IEEE DOI 1009
Depth map See also Fusing remote sensing images using a trous wavelet transform and empirical mode decomposition. BibRef

Herbort, S.[Steffen], Gerken, B.[Britta], Schugk, D.[Daniel], Wöhler, C.[Christian],
3D range scan enhancement using image-based methods,
PandRS(84), No. 0, 2013, pp. 69-84.
Elsevier DOI 1309
Photometry BibRef

Yang, Q.X.[Qing-Xiong], Ahuja, N., Yang, R.G.[Rui-Gang], Tan, K.H.[Kar-Han], Davis, J., Culbertson, B., Apostolopoulos, J., Wang, G.[Gang],
Fusion of Median and Bilateral Filtering for Range Image Upsampling,
IP(22), No. 12, 2013, pp. 4841-4852.
IEEE DOI 1312
image colour analysis BibRef

Park, J.[Jaesik], Kim, H.W.[Hyeong-Woo], Tai, Y.W.[Yu-Wing], Brown, M.S.[Michael S.], Kweon, I.S.[In So],
High-Quality Depth Map Upsampling and Completion for RGB-D Cameras,
IP(23), No. 12, December 2014, pp. 5559-5572.
IEEE DOI 1412
BibRef
Earlier:
High quality depth map upsampling for 3D-TOF cameras,
ICCV11(1623-1630).
IEEE DOI 1201
cameras. Upsample ToF camera using high-res image. BibRef

Kang, M.K.[Min-Koo], Kim, D.Y.[Dae-Young], Yoon, K.J.[Kuk-Jin],
Adaptive Support of Spatial-Temporal Neighbors for Depth Map Sequence Up-sampling,
SPLetters(21), No. 2, February 2014, pp. 150-154.
IEEE DOI 1402
Markov processes BibRef

Kang, M.K.[Min-Koo], Yoon, K.J.[Kuk-Jin],
Depth-Discrepancy-Compensated Inter-Prediction With Adaptive Segment Management for Multiview Depth Video Coding,
MultMed(16), No. 6, October 2014, pp. 1563-1573.
IEEE DOI 1410
statistical analysis BibRef

Kim, J.[Joohyeok], Jeon, G.G.[Gwang-Gil], Jeong, J.C.[Je-Chang],
Joint-adaptive bilateral depth map upsampling,
SP:IC(29), No. 4, 2014, pp. 506-513.
Elsevier DOI 1404
Depth upsampling BibRef

Choi, J.[Jinwook], Min, D.B.[Dong-Bo], Sohn, K.H.[Kwang-Hoon],
Reliability-Based Multiview Depth Enhancement Considering Interview Coherence,
CirSysVideo(24), No. 4, April 2014, pp. 603-616.
IEEE DOI 1405
image colour analysis BibRef

Choi, O.[Ouk], Jung, S.W.[Seung-Won],
A Consensus-Driven Approach for Structure and Texture Aware Depth Map Upsampling,
IP(23), No. 8, August 2014, pp. 3321-3335.
IEEE DOI 1408
image colour analysis BibRef

Wang, Y.[Yanke], Zhong, F.[Fan], Peng, Q.S.[Qun-Sheng], Qin, X.Y.[Xue-Ying],
Depth map enhancement based on color and depth consistency,
VC(30), No. 10, October 2014, pp. 1157-1168.
WWW Link. 1410
BibRef

Huang, W.Q.[Wen-Qi], Gong, X.J.[Xiao-Jin], Yang, M.Y.,
Joint Object Segmentation and Depth Upsampling,
SPLetters(22), No. 2, February 2015, pp. 192-196.
IEEE DOI 1410
Markov processes BibRef

Zhu, X., Song, X., Chen, X.,
Image Guided Depth Map Upsampling using Anisotropic TV-L2,
SPLetters(22), No. 3, March 2015, pp. 318-321.
IEEE DOI 1410
Cameras BibRef

Jung, S.W.[Seung-Won], Choi, O.[Ouk],
Learning-Based Filter Selection Scheme for Depth Image Super Resolution,
CirSysVideo(24), No. 10, October 2014, pp. 1641-1650.
IEEE DOI 1411
feature extraction BibRef

Wan, P.F.[Peng-Fei], Cheung, G.[Gene], Chou, P.A., Florencio, D., Zhang, C.[Cha], Au, O.C.,
Precision Enhancement of 3-D Surfaces from Compressed Multiview Depth Maps,
SPLetters(22), No. 10, October 2015, pp. 1676-1680.
IEEE DOI 1506
data compression BibRef

Liu, W.[Wei], Jia, S.[Shaoyong], Li, P.[Penglin], Chen, X.G.[Xiao-Gang], Yang, J.[Jie], Wu, Q.A.[Qi-Ang],
An MRF-Based Depth Upsampling: Upsample the Depth Map With Its Own Property,
SPLetters(22), No. 10, October 2015, pp. 1708-1712.
IEEE DOI 1506
Markov processes BibRef

Liu, W.[Wei], Li, P.[Penglin], Yang, J.[Jie], Shi, P.F.[Peng-Fei],
Upsampling the depth map with its own properties,
ICIP15(3530-3534)
IEEE DOI 1512
Bilateral filter;ToF;depth map upsampling;optimization BibRef

Liu, W.[Wei], Chen, X.G.[Xiao-Gang], Yang, J.[Jie], Wu, Q.A.[Qi-Ang],
Robust Color Guided Depth Map Restoration,
IP(26), No. 1, January 2017, pp. 315-327.
IEEE DOI 1612
image colour analysis BibRef

Xie, J.[Jun], Feris, R.S.[Rogerio Schmidt], Yu, S.S.[Shiaw-Shian], Sun, M.T.[Ming-Ting],
Joint Super Resolution and Denoising From a Single Depth Image,
MultMed(17), No. 9, September 2015, pp. 1525-1537.
IEEE DOI 1509
edge detection BibRef

Xie, J.[Jun], Feris, R.S.[Rogerio Schmidt], Sun, M.T.[Ming-Ting],
Edge-Guided Single Depth Image Super Resolution,
IP(25), No. 1, January 2016, pp. 428-438.
IEEE DOI 1601
BibRef
Earlier: ICIP14(3773-37777)
IEEE DOI 1502
edge detection BibRef

Kiechle, M.[Martin], Habigt, T.[Tim], Hawe, S.[Simon], Kleinsteuber, M.[Martin],
A Bimodal Co-sparse Analysis Model for Image Processing,
IJCV(114), No. 2-3, September 2015, pp. 233-247.
Springer DOI 1509
BibRef
Earlier: A1, A3, A4, Only:
A Joint Intensity and Depth Co-sparse Analysis Model for Depth Map Super-resolution,
ICCV13(1545-1552)
IEEE DOI 1403
BibRef

Xu, Z.[Zekai], Wang, X.W.[Xue-Wen], Chen, Z.X.[Zi-Xuan], Xiong, D.P.[Dong-Ping], Ding, M.[Mingyue], Hou, W.G.[Wen-Guang],
Nonlocal similarity based DEM super resolution,
PandRS(110), No. 1, 2015, pp. 48-54.
Elsevier DOI 1601
Digital elevation model BibRef

Wang, Q., Li, S., Qin, H., Hao, A.,
Super-Resolution of Multi-Observed RGB-D Images Based on Nonlocal Regression and Total Variation,
IP(25), No. 3, March 2016, pp. 1425-1440.
IEEE DOI 1602
Image edge detection BibRef

He, H., Mandal, S., Buehler, A., Deán-Ben, X.L., Razansky, D., Ntziachristos, V.,
Improving Optoacoustic Image Quality via Geometric Pixel Super-Resolution Approach,
MedImg(35), No. 3, March 2016, pp. 812-818.
IEEE DOI 1603
Detectors BibRef

Huo, Y., Yang, F.,
High-dynamic range image generation from single low-dynamic range image,
IET-IP(10), No. 3, 2016, pp. 198-205.
DOI Link 1603
image enhancement BibRef

Hua, K.L.[Kai-Lung], Lo, K.H.[Kai-Han], Wang, Y.C.F.[Y.C. Frank],
Extended Guided Filtering for Depth Map Upsampling,
MultMedMag(23), No. 2, April 2016, pp. 72-83.
IEEE DOI 1605
Cameras. filtering theory BibRef

Lo, K.H.[Kai-Han], Wang, Y.C.F.[Y.C. Frank], Hua, K.L.[Kai-Lung],
Edge-Preserving Depth Map Upsampling by Joint Trilateral Filter,
Cyber(48), No. 1, January 2018, pp. 371-384.
IEEE DOI 1801
BibRef
Earlier:
Joint trilateral filtering for depth map super-resolution,
VCIP13(1-6)
IEEE DOI 1402
Color, Image color analysis, Image edge detection, Image resolution, Image sensors, Kernel, Sensors, range sensor BibRef

Al Ismaeil, K.[Kassem], Aouada, D.[Djamila], Mirbach, B.[Bruno], Ottersten, B.[Björn],
Enhancement of dynamic depth scenes by upsampling for precise super-resolution (UP-SR),
CVIU(147), No. 1, 2016, pp. 38-49.
Elsevier DOI 1605
BibRef
Earlier:
Dynamic super resolution of depth sequences with non-rigid motions,
ICIP13(660-664)
IEEE DOI 1402
Super-resolution BibRef

Al Ismaeil, K.[Kassem], Aouada, D.[Djamila], Solignac, T.[Thomas], Mirbach, B.[Bruno], Ottersten, B.[Bjorn],
Real-Time Enhancement of Dynamic Depth Videos with Non-Rigid Deformations,
PAMI(39), No. 10, October 2017, pp. 2045-2059.
IEEE DOI 1709
BibRef
Earlier:
Real-time non-rigid multi-frame depth video super-resolution,
FusionDynamic15(8-16)
IEEE DOI 1510
Cameras, Heuristic algorithms, Image resolution, Real-time systems, Three-dimensional displays, Two dimensional displays, Videos, Depth enhancement, Kalman filtering, bilateral total variation, non-rigid deformations, registration, super-resolution BibRef

Sharma, R.[Rahil], Xu, Z.[Zewei], Sugumaran, R.[Ramanathan], Oliveira, S.[Suely],
Parallel Landscape Driven Data Reduction & Spatial Interpolation Algorithm for Big LiDAR Data,
IJGI(5), No. 6, 2016, pp. 97.
DOI Link 1608
BibRef

Yuan, Y.[Ying], Wang, X.R.[Xiao-Rui], Zhang, J.L.[Jian-Lei], Wu, X.X.[Xiong-Xiong], Zhang, Y.[Yan],
Feasibility study for super-resolution 3D integral imaging using time-multiplexed compressive coding,
JOSA-A(33), No. 7, July 2016, pp. 1377-1384.
DOI Link 1608
Superresolution BibRef

Arslan, M.T.[Musa Tunç], Tofighi, M.[Mohammad], Çetin, A.E.[A. Enis],
Range resolution improvement in FM-based passive radars using deconvolution,
SIViP(10), No. 8, November 2016, pp. 1481-1488.
WWW Link. 1610
BibRef

Jin, X.[Xin], Xu, Y.[Yatong], Dai, Q.H.[Qiong-Hai],
Depth dithering based on texture edge-assisted classification,
SP:IC(47), No. 1, 2016, pp. 56-71.
Elsevier DOI 1610
Depth denoising BibRef

Mandal, S.[Srimanta], Bhavsar, A.[Arnav], Sao, A.K.[Anil Kumar],
Depth Map Restoration From Undersampled Data,
IP(26), No. 1, January 2017, pp. 119-134.
IEEE DOI 1612
BibRef
Earlier:
Hierarchical example-based range-image super-resolution with edge-preservation,
ICIP14(3867-3871)
IEEE DOI 1502
image representation. Cameras BibRef

Jung, C.[Cheolkon], Yu, S.T.[Sheng-Tao], Kim, J.[Joongkyu],
Intensity-guided edge-preserving depth upsampling through weighted L0 gradient minimization,
JVCIR(42), No. 1, 2017, pp. 132-144.
Elsevier DOI 1701
BibRef
Earlier: A2, A1, A3:
Color-guided boundary-preserving depth upsampling based on L0 gradient minimization,
VCIP16(1-4)
IEEE DOI 1701
Depth upsampling. Cameras BibRef

Kamilov, U.S., Boufounos, P.T.,
Motion-Adaptive Depth Superresolution,
IP(26), No. 4, April 2017, pp. 1723-1731.
IEEE DOI 1704
computer vision BibRef

Lei, J., Li, L., Yue, H., Wu, F., Ling, N., Hou, C.,
Depth Map Super-Resolution Considering View Synthesis Quality,
IP(26), No. 4, April 2017, pp. 1732-1745.
IEEE DOI 1704
image resolution BibRef

Eichhardt, I.[Iván], Chetverikov, D.[Dmitry], Jankó, Z.[Zsolt],
Image-guided ToF depth upsampling: a survey,
MVA(28), No. 3-4, May 2017, pp. 267-282.
WWW Link. 1704
Survey, Depth Super Resolution. BibRef

Yuan, L.[Liang], Jin, X.[Xin], Li, Y.G.[Yang-Guang], Yuan, C.[Chun],
Depth map super-resolution via low-resolution depth guided joint trilateral up-sampling,
JVCIR(46), No. 1, 2017, pp. 280-291.
Elsevier DOI 1706
Joint, trilateral, upsampling BibRef

Li, Y.G.[Yang-Guang], Zhang, L.[Lei], Zhang, Y.B.[Yong-Bing], Xuan, H.M.[Hui-Ming], Dai, Q.H.[Qiong-Hai],
Depth map super-resolution via iterative joint-trilateral-upsampling,
VCIP14(386-389)
IEEE DOI 1504
image colour analysis BibRef

Lv, H.J.[Hui-Jin], Zhang, Y.B.[Yong-Bing], Li, K.[Kai], Wang, X.Z.[Xing-Zheng], Xuan, H.M.[Hui-Ming], Dai, Q.H.[Qiong-Hai],
Synthesis-guided depth super resolution,
VCIP14(125-128)
IEEE DOI 1504
image enhancement BibRef

Liu, W., Chen, X., Yang, J., Wu, Q.,
Variable Bandwidth Weighting for Texture Copy Artifact Suppression in Guided Depth Upsampling,
CirSysVideo(27), No. 10, October 2017, pp. 2072-2085.
IEEE DOI 1710
Bandwidth, Color, Computational efficiency, DH-HEMTs, Image color analysis, Image resolution, Kernel, Blur of depth discontinuities, color image-guided depth upsampling, texture copy artifacts, variable, bandwidth, weighting BibRef

Shabaninia, E.[Elham], Naghsh-Nilchi, A.R.[Ahmad Reza], Kasaei, S.[Shohreh],
High-order Markov random field for single depth image super-resolution,
IET-CV(11), No. 8, December 2017, pp. 683-690.
DOI Link 1712
BibRef

Jiang, Z., Hou, Y., Yue, H., Yang, J., Hou, C.,
Depth Super-Resolution From RGB-D Pairs With Transform and Spatial Domain Regularization,
IP(27), No. 5, May 2018, pp. 2587-2602.
IEEE DOI 1804
autoregressive processes, finite difference methods, gradient methods, image colour analysis, image resolution, sparse representation BibRef

Cruz-Martinez, C.[Claudia], Martínez-Carranza, J.[José], Mayol-Cuevas, W.W.[Walterio W.],
Real-time enhancement of sparse 3D maps using a parallel segmentation scheme based on superpixels,
RealTimeIP(14), No. 3, March 2018, pp. 667-683.
Springer DOI 1804
BibRef

Wang, Y., Zhang, J., Liu, Z., Wu, Q., Zhang, Z., Jia, Y.,
Depth Super-Resolution on RGB-D Video Sequences With Large Displacement 3D Motion,
IP(27), No. 7, July 2018, pp. 3571-3585.
IEEE DOI 1805
Boolean functions, Data structures, Image resolution, Motion compensation, Optical imaging, large displacement 3D motion BibRef

Chang, T.A.[Ting-An], Yang, J.F.[Jar-Ferr],
Precise depth map upsampling and enhancement based on edge-preserving fusion filters,
IET-CV(12), No. 5, August 2018, pp. 651-658.
DOI Link 1807
BibRef

Huang, X.[Xu], Qin, R.[Rongjun], Xiao, C.[Changlin], Lu, X.[Xiaohu],
Super resolution of laser range data based on image-guided fusion and dense matching,
PandRS(144), 2018, pp. 105-118.
Elsevier DOI 1809
Super resolution, Laser range data, Image, Fusion, Matching BibRef

Zhang, H., Zhang, Y., Wang, H., Ho, Y., Feng, S.,
WLDISR: Weighted Local Sparse Representation-Based Depth Image Super-Resolution for 3D Video System,
IP(28), No. 2, February 2019, pp. 561-576.
IEEE DOI 1811
edge detection, image colour analysis, image reconstruction, image representation, image resolution, image texture, virtual view image quality BibRef

Wen, Y., Sheng, B., Li, P., Lin, W., Feng, D.D.,
Deep Color Guided Coarse-to-Fine Convolutional Network Cascade for Depth Image Super-Resolution,
IP(28), No. 2, February 2019, pp. 994-1006.
IEEE DOI 1811
Image color analysis, Image edge detection, Color, Spatial resolution, Kernel, Sensors, Depth super-resolution, filter kernel learning BibRef


Yan, S.[Shi], Wu, C.L.[Cheng-Lei], Wang, L.[Lizhen], Xu, F.[Feng], An, L.[Liang], Guo, K.[Kaiwen], Liu, Y.B.[Ye-Bin],
DDRNet: Depth Map Denoising and Refinement for Consumer Depth Cameras Using Cascaded CNNs,
ECCV18(X: 155-171).
Springer DOI 1810
BibRef

Jeon, J.[Junho], Lee, S.Y.[Seung-Yong],
Reconstruction-Based Pairwise Depth Dataset for Depth Image Enhancement Using CNN,
ECCV18(XVI: 438-454).
Springer DOI 1810
BibRef

Rapp, J., Dawson, R.M.A., Goyal, V.K.,
Improving LIDAR Depth Resolution with Dither,
ICIP18(1553-1557)
IEEE DOI 1809
Laser radar, Quantization (signal), Photonics, Laser modes, Laser noise, Measurement by laser beam, Detectors, generalized Gaussian BibRef

Bolsee, Q., Munteanu, A.,
CNN-based Denoising of Time-Of-Flight Depth Images,
ICIP18(510-514)
IEEE DOI 1809
Noise reduction, Training, Convolution, Sensors, Cameras, Filtering, Gaussian noise, Time-of-Flight, denoising, residual learning, Convolutional Neural Network BibRef

Garcia, D.C., Fonseca, T.A., de Queiroz, R.L.,
Example-Based Super-Resolution for Point-Cloud Video,
ICIP18(2959-2963)
IEEE DOI 1809
Signal resolution, Spatial resolution, Gain, Measurement, Octrees, super-resolution (SR) BibRef

Chen, R., Zhai, D., Liu, X., Zhao, D.,
Noise-Aware Super-Resolution of Depth Maps Via Graph-Based Plug-And-Play Framework,
ICIP18(2536-2540)
IEEE DOI 1809
Image resolution, Laplace equations, Task analysis, Image restoration, Image edge detection, graph signal processing BibRef

Xu, D., Fan, X., Zhao, D., Gao, W.,
Multiresolution Contourlet Transform Fusion Based Depth Map Super Resolution,
ICIP18(2187-2191)
IEEE DOI 1809
Transforms, Spatial resolution, Color, Laplace equations, Fans, contourlet transform, fusion, super resolution BibRef

Jin, Z., Luo, L., Tang, Y., Zou, W., Li, X.,
A CNN cascade for quality enhancement of compressed depth images,
VCIP17(1-4)
IEEE DOI 1804
convolution, data compression, feedforward neural nets, filtering theory, image coding, image denoising, image recognition, Quality enhancement BibRef

Boubou, S.[Somar], Narikiyo, T.[Tatsuo], Kawanishi, M.[Michihiro],
Adaptive filter for denoising 3D data captured by depth sensors,
3DTV-CON17(1-4)
IEEE DOI 1804
adaptive filters, object recognition, signal denoising, spatial variables measurement, support vector machines, 3D depth sensors BibRef

Li, J., You, S., Robles-Kelly, A.,
Stereo Super-Resolution via a Deep Convolutional Network,
DICTA17(1-7)
IEEE DOI 1804
convolution, image resolution, learning (artificial intelligence), neural nets, Training BibRef

Yang, J., Lan, H., Song, X., Li, K.,
Depth super-resolution via fully edge-augmented guidance,
VCIP17(1-4)
IEEE DOI 1804
edge detection, feedforward neural nets, image colour analysis, image resolution, learning (artificial intelligence), CNNs, fully guidance structure BibRef

Xu, W., Wang, J., Zhu, Q., Wu, X., Qi, Y.,
Depth map super-resolution via multiclass dictionary learning with geometrical directions,
VCIP17(1-4)
IEEE DOI 1804
autoregressive processes, image colour analysis, image reconstruction, image representation, image resolution, super-resolution (SR) BibRef

Tsuchiya, A., Sugimura, D., Hamamoto, T.,
Depth upsampling by depth prediction,
ICIP17(1662-1666)
IEEE DOI 1803
Cameras, Color, DH-HEMTs, Estimation, Image color analysis, Image sequences, Motion estimation, Depth prediction, Spatio-temporal coherency BibRef

Zhang, Y., Zhou, Y., Wang, A., Wu, Q., Hou, C.,
Joint nonlocal sparse representation for depth map super-resolution,
ICIP17(972-976)
IEEE DOI 1803
Color, Dictionaries, Estimation, Image reconstruction, Principal component analysis, Spatial resolution, sparse representation BibRef

Zhang, H.T., Yu, J., Wang, Z.F.,
Depth map super-resolution using non-local higher-order regularization with classified weights,
ICIP17(4043-4047)
IEEE DOI 1803
Adaptation models, Color, Feature extraction, Image color analysis, Image edge detection, Image resolution, Tuning, non-local generalized total variation BibRef

Zhu, J., Zhang, J., Cao, Y., Wang, Z.,
Image guided depth enhancement via deep fusion and local linear regularizaron,
ICIP17(4068-4072)
IEEE DOI 1803
Color, Correlation, Feature extraction, Image edge detection, Image resolution, Noise reduction, Training, deep feature space, local linear regularization BibRef

Zhu, J.[Jiang], Zhai, W.[Wei], Cao, Y.[Yang], Zha, Z.J.[Zheng-Jun],
Co-occurrent Structural Edge Detection for Color-Guided Depth Map Super-Resolution,
MMMod18(I:93-105).
Springer DOI 1802
BibRef

Peng, S., Haefner, B., Quéau, Y., Cremers, D.,
Depth Super-Resolution Meets Uncalibrated Photometric Stereo,
CVPV17(2961-2968)
IEEE DOI 1802
Harmonic analysis, Image resolution, Lighting, Mathematical model, Shape, Signal resolution, Standards BibRef

Shiba, Y., Ono, S., Furukawa, R., Hiura, S., Kawasaki, H.,
Temporal Shape Super-Resolution by Intra-frame Motion Encoding Using High-fps Structured Light,
ICCV17(115-123)
IEEE DOI 1802
calibration, cameras, image motion analysis, image reconstruction, image resolution, image sensors, image sequences, BibRef

Gu, S., Zuo, W., Guo, S., Chen, Y., Chen, C., Zhang, L.,
Learning Dynamic Guidance for Depth Image Enhancement,
CVPR17(712-721)
IEEE DOI 1711
Analytical models, Computational modeling, Image enhancement, Image resolution, Sensors, Training, data BibRef

Mieloch, D., Dziembowski, A., Grzelka, A., Stankiewicz, O., Domanski, M.,
Temporal enhancement of graph-based depth estimation method,
WSSIP17(1-4)
IEEE DOI 1707
Cameras, Estimation, Image processing, Motion segmentation, Optimization, Three-dimensional displays, Transform coding, Depth estimation, Image segmentation, Temporal, consistency BibRef

Konno, Y., Tanaka, M., Okutomi, M., Yanagawa, Y., Kinoshita, K., Kawade, M.,
Depth map upsampling by self-guided residual interpolation,
ICPR16(1394-1399)
IEEE DOI 1705
Algorithm design and analysis, Art, Estimation, Image resolution, Indexes, Interpolation, Sensors BibRef

Song, X., Huang, H., Zhong, F., Ma, X., Qin, X.,
Edge-guided depth map enhancement,
ICPR16(2758-2763)
IEEE DOI 1705
Color, Image color analysis, Image edge detection, Noise measurement, Optimization, Sensors, Tensile, stress BibRef

Song, X.[Xibin], Dai, Y.[Yuchao], Qin, X.[Xueying],
Deep Depth Super-Resolution: Learning Depth Super-Resolution Using Deep Convolutional Neural Network,
ACCV16(IV: 360-376).
Springer DOI 1704
BibRef

Ye, X.C.[Xin-Chen], Song, X.L.[Xiao-Lin], Yang, J.Y.[Jing-Yu], Hou, C.P.[Chun-Ping], Wang, Y.[Yao],
Depth recovery via decomposition of polynomial and piece-wise constant signals,
VCIP16(1-4)
IEEE DOI 1701
Color BibRef

Zhang, H.T., Kang, K., Wang, Z.F.,
Image guided depth map superresolution using non-local total generalized variation,
VCIP16(1-4)
IEEE DOI 1701
Cameras BibRef

Fu, M., Zhou, W.,
Depth map super-resolution via extended weighted mode filtering,
VCIP16(1-4)
IEEE DOI 1701
Histograms BibRef

Dong, Y., Lin, C., Zhao, Y., Yao, C., Hou, J.,
Depth map up-sampling with texture edge feature via sparse representation,
VCIP16(1-4)
IEEE DOI 1701
Color BibRef

Schneider, N.[Nick], Schneider, L.[Lukas], Pinggera, P.[Peter], Franke, U.[Uwe], Pollefeys, M.[Marc], Stiller, C.[Christoph],
Semantically Guided Depth Upsampling,
GCPR16(37-48).
Springer DOI 1611
BibRef

Akcay, O., Erenoglu, R.C., Erenoglu, O.,
Correction and Densification of UAS-Based Photogrammetric Thermal Point Cloud,
ISPRS16(B3: 163-166).
DOI Link 1610
BibRef

Fukushima, N., Takeuchi, K., Kojima, A.,
Self-similarity matching with predictive linear upsampling for depth map,
3DTV-CON16(1-4)
IEEE DOI 1610
edge detection BibRef

Uruma, K., Konishi, K., Takahashi, T., Furukawa, T.,
High resolution depth image recovery algorithm based on the modeling of the sum of an average distance image and a surface image,
ICIP16(2836-2840)
IEEE DOI 1610
Cameras BibRef

Krishnamurthy, S., Ramakrishnan, K.R.,
Image-guided depth map upsampling using normalized cuts-based segmentation and smoothness priors,
ICIP16(554-558)
IEEE DOI 1610
Color BibRef

Liu, W., Chen, X., Yang, J., Wu, Q.,
Robust weighted least squares for guided depth upsampling,
ICIP16(559-563)
IEEE DOI 1610
Color BibRef

Ferstl, D.[David], Rother, M., Bischof, H.,
Variational Depth Superresolution Using Example-Based Edge Representations,
ICCV15(513-521)
IEEE DOI 1602
Dictionaries BibRef

Riegler, G.[Gernot], Ferstl, D.[David], Rüther, M.[Matthias], Bischof, H.[Horst],
A Deep Primal-Dual Network for Guided Depth Super-Resolution,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Riegler, G.[Gernot], Rüther, M.[Matthias], Bischof, H.[Horst],
ATGV-Net: Accurate Depth Super-Resolution,
ECCV16(III: 268-284).
Springer DOI 1611
BibRef

Riegler, G.[Gernot], Ranftl, R.[René], Rüther, M.[Matthias], Pock, T.[Thomas], Bischof, H.[Horst],
Depth Restoration via Joint Training of a Global Regression Model and CNNs,
BMVC15(xx-yy).
DOI Link 1601
Denoising and upscaling of depth maps. BibRef

Kim, Y.J.[Young-Jung], Choi, S.[Sunghwan], Oh, C.[Changjae], Sohn, K.H.[Kwang-Hoon],
A majorize-minimize approach for high-quality depth upsampling,
ICIP15(392-396)
IEEE DOI 1512
Depth map upsampling BibRef

Deng, X.W.[Xiao-Wei], Wu, X.L.[Xiao-Lin],
Sparsity-based depth image restoration using surface priors and RGB-D correlations,
ICIP15(3881-3885)
IEEE DOI 1512
Depth image; image restoration; sparsity; superresolution BibRef

Zuo, Y.[Yifan], An, P.[Ping], Zheng, S.[Shuai], Zhang, Z.Y.[Zhao-Yang],
Depth upsampling method via Markov random fields without edge-misaligned artifacts,
ICIP15(2324-2328)
IEEE DOI 1512
Markov Random Field (MRF); depth map upsampling; depth recovery BibRef

Schedl, D.C., Birklbauer, C., Bimber, O.,
Directional Super-Resolution by Means of Coded Sampling and Guided Upsampling,
ICCP15(1-10)
IEEE DOI 1511
cameras BibRef

Lu, J.J.[Jia-Jun], Forsyth, D.A.[David A.],
Sparse depth super resolution,
CVPR15(2245-2253)
IEEE DOI 1510
BibRef

Kwon, H.[Hyeok_Hyen], Tai, Y.W.[Yu-Wing], Lin, S.[Stephen],
Data-driven depth map refinement via multi-scale sparse representation,
CVPR15(159-167)
IEEE DOI 1510
BibRef

Herrera, J.L., del-Blanco, C.R., Garcia, N.,
Edge-based depth gradient refinement for 2D to 3D learned prior conversion,
3DTV-CON15(1-4)
IEEE DOI 1508
Clustering algorithms BibRef

Schoenenberger, Y., Paratte, J., Vandergheynst, P.,
Graph-based denoising for time-varying point clouds,
3DTV-CON15(1-4)
IEEE DOI 1508
Manifolds BibRef

Lee, G.G.C., Li, B.S.[Bo-Syun], Chen, C.F.[Chun-Fu],
Content-adaptive depth map enhancement based on motion distribution,
VCIP14(482-485)
IEEE DOI 1504
filtering theory BibRef

Joachimiak, M.[Michal], Aflaki, P.[Payman], Hannuksela, M.M.[Miska M.], Gabbouj, M.[Moncef],
Evaluation of Depth-Based Super Resolution on Compressed Mixed Resolution 3D Video,
BD3DCV14(227-237).
Springer DOI 1504
BibRef

Vianello, A., Michielin, F., Calvagno, G., Sartor, P., Erdler, O.,
Depth images super-resolution: An iterative approach,
ICIP14(3778-3782)
IEEE DOI 1502
Cameras;Color;Noise;Spatial resolution;Standards;Stereo vision BibRef

dos Santos, L.T.A.[Leandro Tavares Aragão], Loaiza Fernandez, M.E.[Manuel Eduardo], Raposo, A.B.[Alberto Barbosa],
Generating Super-Resolved Depth Maps Using Low-Cost Sensors and RGB Images,
ISVC14(II: 632-641).
Springer DOI 1501
BibRef

Li, L.[Li], Zhang, C.M.[Cai-Ming],
A Nonlocal Filter-Based Hybrid Strategy for Depth Map Enhancement,
ICPR14(4394-4399)
IEEE DOI 1412
Color BibRef

Wang, Y.C.[Yu-Cheng], Di, H.[Huijun], Wang, B.[Bingjie], Liang, W.[Wei], Zhang, J.[Jian], Jia, Y.D.[Yun-De],
Depth Super-resolution by Fusing Depth Imaging and Stereo Vision with Structural Determinant Information Inference,
ICPR14(4212-4217)
IEEE DOI 1412
Art BibRef

Ghesu, F.C.[Florin C.], Köhler, T.[Thomas], Haase, S.[Sven], Hornegger, J.[Joachim],
Guided Image Super-Resolution: A New Technique for Photogeometric Super-Resolution in Hybrid 3-D Range Imaging,
GCPR14(227-238).
Springer DOI 1411
BibRef

Hui, T.W.[Tak-Wai], Ngan, K.N.[King Ngi],
Motion-Depth: RGB-D Depth Map Enhancement with Motion and Depth in Complement,
CVPR14(3962-3969)
IEEE DOI 1409
BibRef
And:
Dense depth map generation using sparse depth data from normal flow,
ICIP14(3837-3841)
IEEE DOI 1502
BibRef
And:
Depth enhancement using RGB-D guided filtering,
ICIP14(3832-3836)
IEEE DOI 1502
Cameras. Approximation methods BibRef

Rana, P.K., Taghia, J., Flierl, M.,
Statistical methods for inter-view depth enhancement,
3DTV-CON14(1-4)
IEEE DOI 1409
image enhancement BibRef

Gong, X.J.[Xiao-Jin], Ren, J.Q.[Jian-Qiang], Lai, B.S.[Bai-Sheng], Yan, C.H.[Chao-Hua], Qian, H.[Hui],
Guided Depth Upsampling via a Cosparse Analysis Model,
FusionOutdoor14(738-745)
IEEE DOI 1409
Guided depth upsampling BibRef

Correia, P., Marcelino, S., Assuncao, P., Faria, S., Soares, S., Pagliari, C., da Silva, E.,
Enhancement method for multiple description decoding of depth maps subject to random loss,
3DTV-CON14(1-4)
IEEE DOI 1409
decoding BibRef

Li, J.[Jing], Lu, Z.C.[Zhi-Chao], Zeng, G.[Gang], Gan, R.[Rui], Zha, H.B.[Hong-Bin],
Similarity-Aware Patchwork Assembly for Depth Image Super-resolution,
CVPR14(3374-3381)
IEEE DOI 1409
Assembly; Disassemble; Dpeth map super resolution; Self-similarity BibRef

Joachimiak, M., Hannuksela, M.M., Gabbouj, M.,
View synthesis quality mapping for depth-based super resolution on mixed resolution 3D video,
3DTV-CON14(1-4)
IEEE DOI 1409
image resolution BibRef

Dai, L.Q.[Long-Quan], Wang, H.X.[Hao-Xing], Mei, X.[Xing], Zhang, X.P.[Xiao-Peng],
Depth Map Upsampling via Compressive Sensing,
ACPR13(90-94)
IEEE DOI 1408
compressed sensing BibRef

Ferstl, D.[David], Reinbacher, C.[Christian], Ranftl, R.[Rene], Ruether, M.[Matthias], Bischof, H.[Horst],
Image Guided Depth Upsampling Using Anisotropic Total Generalized Variation,
ICCV13(993-1000)
IEEE DOI 1403
anisotropic tensor BibRef

Silva, J.W.[Jong Wan], Gomes, L.[Leonardo], Aguero, K.A.[Karl Apaza], Bellon, O.R.P.[Olga R.P.], Silva, L.[Luciano],
Real-time acquisition and super-resolution techniques on 3D reconstruction,
ICIP13(2135-2139)
IEEE DOI 1402
3D reconstruction;real-time;super-resolution BibRef

Zheng, H., Bouzerdoum, A., Phung, S.L.,
Depth image super-resolution using multi-dictionary sparse representation,
ICIP13(957-961)
IEEE DOI 1402
Cameras BibRef

Davoodianidaliki, M., Saadatseresht, M.,
Three Pre-Processing Steps to Increase the Quality of Kinect Range Data,
SMPR13(127-132).
HTML Version. 1311
BibRef

Ismaeil, K.A.[Kassem Al], Aouada, D.[Djamila],
Depth Super-Resolution by Enhanced Shift and Add,
CAIP13(II:100-107).
Springer DOI 1311
BibRef

Liu, M.Y.[Ming-Yu], Tuzel, O.[Oncel], Taguchi, Y.[Yuichi],
Joint Geodesic Upsampling of Depth Images,
CVPR13(169-176)
IEEE DOI 1309
depth; filtering; geodesic; upsampling BibRef

Yu, L.F.[Lap-Fai], Yeung, S.K.[Sai-Kit], Tai, Y.W.[Yu-Wing], Lin, S.[Stephen],
Shading-Based Shape Refinement of RGB-D Images,
CVPR13(1415-1422)
IEEE DOI 1309
BibRef

Hornacek, M.[Michael], Rhemann, C.[Christoph], Gelautz, M.[Margrit], Rother, C.[Carsten],
Depth Super Resolution by Rigid Body Self-Similarity in 3D,
CVPR13(1123-1130)
IEEE DOI 1309
dense matching; depth super resolution; optimization BibRef

Kim, J., Lee, J.K., Lee, K.M.,
Deeply-Recursive Convolutional Network for Image Super-Resolution,
CVPR16(1637-1645)
IEEE DOI 1612
BibRef

Lim, B., Son, S., Kim, H., Nah, S., Lee, K.M.,
Enhanced Deep Residual Networks for Single Image Super-Resolution,
NTIRE17(1132-1140)
IEEE DOI 1709
Computational modeling, Computer architecture, Convolution, Image reconstruction, Image resolution, Signal resolution, Training BibRef

Kim, J., Lee, J.K., Lee, K.M.,
Accurate Image Super-Resolution Using Very Deep Convolutional Networks,
CVPR16(1646-1654)
IEEE DOI 1612
BibRef

Lee, H.S.[Hee Seok], Lee, K.M.[Kuoung Mu],
Dense 3D Reconstruction from Severely Blurred Images Using a Single Moving Camera,
CVPR13(273-280)
IEEE DOI 1309
Dense 3D reconstruction; Image deblurring; Visual SLAM BibRef

Lee, H.S.[Hee Seok], Lee, K.M.[Kuoung Mu],
Simultaneous Super-Resolution of Depth and Images Using a Single Camera,
CVPR13(281-288)
IEEE DOI 1309
Dense 3D reconstruction; Image super-resolution; Visual SLAM See also Simultaneous Super-Resolution of Depth and Images Using a Single Camera. BibRef

Nelson, K., Bhatti, A., Nahavandi, S.,
Super-resolution of a 3-dimensional scene from novel viewpoints,
ICARCV12(1380-1385).
IEEE DOI 1304
BibRef

Li, J.[Jing], Lu, Z.C.[Zhi-Chao], Zeng, G.[Gang], Gan, R.[Rui], Wang, L.[Long], Zha, H.B.[Hong-Bin],
A Joint Learning-Based Method for Multi-view Depth Map Super Resolution,
ACPR13(456-460)
IEEE DOI 1408
BibRef
Earlier: A1, A3, A4, A6, A5, Only:
A Bayesian Approach to Uncertainty-Based Depth Map Super Resolution,
ACCV12(IV:205-216).
Springer DOI 1304
image colour analysis BibRef

Schwarz, S.[Sebastian], Sjostrom, M.[Marten], Olsson, R.[Roger],
Incremental depth upscaling using an edge weighted optimization concept,
3DTV12(1-4).
IEEE DOI 1212
BibRef

Aodha, O.M.[Oisin Mac], Campbell, N.D.F.[Neill D. F.], Nair, A.[Arun], Brostow, G.J.[Gabriel J.],
Patch Based Synthesis for Single Depth Image Super-Resolution,
ECCV12(III: 71-84).
Springer DOI 1210
BibRef

Gevrekci, M.[Murat], Pakin, K.[Kubilay],
Depth map super resolution,
ICIP11(3449-3452).
IEEE DOI 1201
BibRef

Edeler, T., Ohliger, K., Hussmann, S., Mertins, A.,
Super resolution of time-of-flight depth images under consideration of spatially varying noise variance,
ICIP09(1185-1188).
IEEE DOI 0911
BibRef

Awatsu, Y.[Yusaku], Kawai, N.[Norihiko], Sato, T.[Tomokazu], Yokoya, N.[Naokazu],
Spatio-temporal Super-Resolution Using Depth Map,
SCIA09(696-705).
Springer DOI 0906
BibRef

Yang, Q.X.[Qing-Xiong], Yang, R.G.[Rui-Gang], Davis, J.W.[James W.], Nister, D.[David],
Spatial-Depth Super Resolution for Range Images,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Zhang, S.[Song], Royer, D.[Dale], Yau, S.T.[Shing-Tung],
High-resolution, real-time-geometry video acquisition,
SigGraph06(Article 110).
WWW Link. BibRef 0600

Zhang, S.[Song], Huang, P.S.[Pei-Sen],
High-Resolution, Real-time 3D Shape Acquisition,
Sensor3D04(28).
IEEE DOI 0406
BibRef

Zhang, S.[Song],
High-Resolution, Real-Time 3-D Shape Measurement,
Ph.D.Thesis, 2005, State University of New York, Stony Brook. BibRef 0500

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Creating Super Resolution Image from Video .


Last update:Nov 17, 2018 at 09:12:27