The DOI matches its Crossref record; 68 of the 69 references it cites were found in a registry or an index, and 1 are not checked yet.
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“These synthesis methods provide a powerful and efficient means of testing a model, and have the added benefit that the resulting images suggest improvements that might be made to the model [11].”
From Multiscale structural similarity for image quality assessment (2004) · cites this paper as [11]
Citations
Cites
A theory for multiresolution signal decomposition: the wavelet representation
Mallat, S. (1989) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.192463 · Cited by 21,463
Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.
Geman, S., & Geman, D. (1984) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1984.4767596 · Cited by 17,949
Information theory and statistical mechanics
Jaynes, E. T. (1957) · Physical Review · doi:10.1103/physrev.106.620 · Cited by 12,931
Orthonormal bases of compactly supported wavelets
Daubechies, I. C. (1988) · Communications on Pure and Applied Mathematics · doi:10.1002/cpa.3160410705 · Cited by 8,143
Relations between the statistics of natural images and the response properties of cortical cells
Field, D. J. (1987) · Journal of the Optical Society of America A · doi:10.1364/josaa.4.002379 · Cited by 3,241
Texture synthesis by non-parametric sampling
Efros, A. A., & Leung, T. K. (1999) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.1999.790383 · Cited by 3,058
Textures: A Photographic Album for Artists and Designers
Hersey, I., & Brodatz, P. (1968) · Leonardo · doi:10.2307/1571915 · Cited by 2,612
The “independent components” of natural scenes are edge filters
Bell, A. J., & Sejnowski, T. J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00121-1 · Cited by 2,201
Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression
Daugman, J. G. (1988) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/29.1644 · Cited by 1,816
Textons, the elements of texture perception, and their interactions
Julesz, B. (1981) · Nature · doi:10.1038/290091a0 · Cited by 1,703
Research works printed but not linked: 6
- Bergen, J.R. and Landy, M.S. 1991. “Computational modeling of visual texture segregation: Computational models of visual processing. M.S. Landy and J.A. Morshon (Eds.). MIT Press, Cambridge, MA, pp. 253–271.
- Bovik, A.C., Clark, M., and Geisler, W.S. 1992. Localized measurements of emergent image frequencies by Gabor wavelets. IEEE Pat. Anal. Mach. Intell., 38:691–712.
- Knutsson, H. and Granlund, G.H. 1983. Texture analysis using twodimensional quadrature filters. In Workshop on Computer Architecture for Pattern Analysis and Image Database Management, IEEE Computer Society, pp. 206–213.
- Portilla, J. and Simoncelli, E. 1999. Texture modeling and synthesis using joint statistics of complex wavelet coefficients. In IEEE Workshop on Statistical and Computational Theories of Vision, Fort Collins, CO. Available at http://www.cis.ohiostate.edu/~szhu/SCTV99.html.
- Portilla, J. and Simoncelli, E. 2000. Image denoising via adjustment ofwavelet coefficient magnitude correlation. In Seventh IEEE Int'l Conf. on Image Proc., Vancouver, September 10– 13. IEEE Computer Society.
- Zetzsche, C., Wegmann, B., and Bart, E. 1993. Nonlinear aspects of primary vision: Entropy reduction beyond decorrelation. In Int'l Symposium, Society for Information Display, Vol. XXIV, pp. 933–936.
Cited by
Sorted by citations
Items 101–200 of 1,000
Review of digital image correlation application to large-scale composite structure testing
Janeliukštis, R., & Chen, X. D. (2021) · Composite Structures · doi:10.1016/j.compstruct.2021.114143 · Cited by 205
Adaptive perceptual color-texture image segmentation
Chen, J., Pappas, T. N., Mojsilović, A., & Rogowitz, B. E. (2005) · IEEE Transactions on Image Processing · doi:10.1109/tip.2005.852204 · Cited by 204
Random Cascades on Wavelet Trees and Their Use in Analyzing and Modeling Natural Images
Wainwright, M. J., Simoncelli, E. P., & Willsky, A. S. (2001) · Applied and Computational Harmonic Analysis · doi:10.1006/acha.2000.0350 · Cited by 203
Self-citationFour Common Conceptual Fallacies in Mapping the Time Course of Recognition
VanRullen, R. (2011) · Frontiers in Psychology · doi:10.3389/fpsyg.2011.00365 · Cited by 199
Image repairing: robust image synthesis by adaptive ND tensor voting
Jia, J., & Tang, C. (2003) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2003.1211414 · Cited by 198
PhaseNet for Video Frame Interpolation
Schaub-Meyer, S., Djelouah, A., McWilliams, B., Sorkine‐Hornung, A., Groß, M. H., & Schroers, C. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00059 · Cited by 196
The Origins and Prevalence of Texture Bias in Convolutional Neural NetworksPreprint
Hermann, K. L., Chen, T., & Kornblith, S. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1911.09071 · Cited by 195
High temporal resolution decoding of object position and category
Carlson, T. A., Hogendoorn, H., Kanai, R., Mesík, J., & Turret, J. (2011) · Journal of Vision · doi:10.1167/11.10.9 · Cited by 193
Modelling and Interpretation of Architecture from Several Images
Dick, A., Torr, P. H. S., & Cipolla, R. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029665.07652.61 · Cited by 191
Guleryuz, O. G. (2006) · IEEE Transactions on Image Processing · doi:10.1109/tip.2005.863057 · Cited by 191
Analysis of Perceptual Expertise in Radiology – Current Knowledge and a New Perspective
Waite, S., Grigorian, A., Alexander, R. G., Macknik, S. L., Carrasco, M., Heeger, D. J., & Martínez‐Conde, S. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00213 · Cited by 189
Low-Level Image Cues in the Perception of Translucent Materials
Fleming, R. W., & Bülthoff, H. (2005) · ACM Transactions on Applied Perception · doi:10.1145/1077399.1077409 · Cited by 189
Image retrieval by texture similarity
Huang, P., & Dai, S. K. (2002) · Pattern Recognition · doi:10.1016/s0031-3203(02)00083-3 · Cited by 188
Landy, M. S., & Graham, N. (2003) · The MIT Press eBooks · doi:10.7551/mitpress/7131.003.0084 · Cited by 187
Riemannian Analysis of Probability Density Functions with Applications in Vision
Srivastava, A., Jermyn, I. H., & Joshi, S. (2007) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2007.383188 · Cited by 183
Arbitrary Style Transfer with Deep Feature Reshuffle
Gu, S., Chen, C., Liao, J., & Yuan, L. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00858 · Cited by 183
Robust and Generalizable Visual Representation Learning via Random ConvolutionsPreprint
Xu, Z., Liu, D., Yang, J., Raffel, C., & Niethammer, M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.13003 · Cited by 182
Self-Invertible 2D Log-Gabor Wavelets
Fischer, S., Šroubek, F., Perrinet, L., Redondo, R., & Cristóbal, G. (2007) · International Journal of Computer Vision · doi:10.1007/s11263-006-0026-8 · Cited by 181
Image Quilting for Texture Synthesis and Transfer
Efros, A. A., & Freeman, W. T. (2023) · ACM eBooks · doi:10.1145/3596711.3596771 · Cited by 178
Image information and visual quality
Sheikh, H. R., & Bovik, A. C. (2004) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2004.1326643 · Cited by 174
Image statistics underlying natural texture selectivity of neurons in macaque V4
Okazawa, G., Tajima, S., & Komatsu, H. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1415146112 · Cited by 173
Gabriel Peyré, A. (2008) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-008-0120-3 · Cited by 173
Accuracy and speed of material categorization in real-world images
Sharan, L., Rosenholtz, R. E., & Adelson, E. H. (2014) · Journal of Vision · doi:10.1167/14.9.12 · Cited by 173
Perceptual qualities and material classes
Fleming, R. W., Wiebel, C. B., & Gegenfurtner, K. R. (2013) · Journal of Vision · doi:10.1167/13.8.9 · Cited by 171
Flexible gating of contextual influences in natural vision
Coen-Cagli, R., Kohn, A., & Schwartz, O. (2015) · Nature Neuroscience · doi:10.1038/nn.4128 · Cited by 166
Learning Texture Manifolds with the Periodic Spatial GANPreprint
Bergmann, U., Jetchev, N., & Vollgraf, R. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1705.06566 · Cited by 164
Wavelet Feature Selection for Image Classification
Huang, K., & Aviyente, S. (2008) · IEEE Transactions on Image Processing · doi:10.1109/tip.2008.2001050 · Cited by 163
Kovačević, J., & Chebira, A. (2007) · now publishers, Inc. eBooks · doi:10.1561/2000000006 · Cited by 163
Reflectance modeling by neural texture synthesis
Aittala, M., Aila, T., & Lehtinen, J. (2016) · ACM Transactions on Graphics · doi:10.1145/2897824.2925917 · Cited by 157
Image Restoration by Matching Gradient Distributions
Cho, T. S., Zitnick, C. L., Joshi, N., Kang, S. B., Szeliski, R., & Freeman, W. T. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2011.166 · Cited by 156
Local Phase Coherence And The Perception of Blur
Wang, Z., Simoncelli, E. P., & Hughes, H. (2003) · Cited by 156
Self-citationBreast cancer diagnosis system based on wavelet analysis and fuzzy-neural
Mousa, R., MUNIB, Q., & Moussa, A. (2005) · Expert Systems with Applications · doi:10.1016/j.eswa.2004.12.028 · Cited by 154
The meaning and structure of scenes
Võ, M. L. ‐. (2021) · Vision Research · doi:10.1016/j.visres.2020.11.003 · Cited by 153
Hiramatsu, C., Goda, N., & Komatsu, H. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.04.056 · Cited by 152
Applied Bayesian Modeling And Causal Inference From Incomplete-Data Perspectives
Gelman, A., & Xiaoli, M. (2014) · Cited by 152
Classification with scattering operators
Bruna, J., & Mallat, S. (2011) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2011.5995635 · Cited by 151
A new framework for complex wavelet transforms
Fernandes, F. C. A., van Spaendonck, R. L. C., & Burrus, C. S. (2003) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2003.812841 · Cited by 151
Oliva, A., Torralba, A. B., & Schyns, P. G. (2006) · ACM Transactions on Graphics · doi:10.1145/1141911.1141919 · Cited by 151
Visualizing and Understanding Deep Texture Representations
Lin, T., & Maji, S. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.305 · Cited by 150
Wavelet-based texture analysis and synthesis using hidden Markov models
Fan, G., & Xia, X.-G. (2003) · IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications · doi:10.1109/tcsi.2002.807520 · Cited by 150
Object Ensemble Processing in Human Anterior-Medial Ventral Visual Cortex
Cant, J. S., & Xu, Y. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.3325-11.2012 · Cited by 147
Rosenholtz, R. E., Jie, H. J., & Ehinger, K. A. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00013 · Cited by 146
Precedence of the Eye Region in Neural Processing of Faces
Issa, E. B., & DiCarlo, J. J. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.2391-12.2012 · Cited by 145
Elucidating the control and development of skin patterning in cuttlefish
Reiter, S., Hülsdunk, P., Woo, T., Lauterbach, M. A., Eberle, J. S., Akay, L. A., Longo, A., Meier‐Credo, J., Kretschmer, F., Langer, J. D., et al. (2018) · Nature · doi:10.1038/s41586-018-0591-3 · Cited by 145
Texture optimization for example-based synthesis
Kwatra, V., Essa, I. A., Bobick, A., & Kwatra, N. (2005) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/1186822.1073263 · Cited by 143
Structural Texture Similarity Metrics for Image Analysis and Retrieval
Zujovic, J., Pappas, T. N., & Neuhoff, D. L. (2013) · IEEE Transactions on Image Processing · doi:10.1109/tip.2013.2251645 · Cited by 142
Guleryuz, O. G. (2006) · IEEE Transactions on Image Processing · doi:10.1109/tip.2005.863055 · Cited by 140
Artificial Neural Networks and Deep Learning in the Visual Arts: a review
Santos, I., Castro, L., Rodríguez-Fernández, N., Torrente-Patiño, Á., & Carballal, A. (2021) · Neural Computing and Applications · doi:10.1007/s00521-020-05565-4 · Cited by 140
Wang, Z., & Simoncelli, E. P. (2008) · Journal of Vision · doi:10.1167/8.12.8 · Cited by 138
Self-citationMultiscale skewed heavy tailed model for texture analysis
Lasmar, N.-E., Stitou, Y., & Berthoumieu, Y. (2009) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2009.5414404 · Cited by 138
Statistical characterization of real-world illumination
Dror, R. O., Willsky, A. S., & Adelson, E. H. (2004) · Journal of Vision · doi:10.1167/4.9.11 · Cited by 138
HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative ModelsPreprint
Zhou, S., Gordon, M., Krishna, R., Narcomey, A., Fei-Fei, L., & Bernstein, M. S. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.01121 · Cited by 135
Visual vibrometry: Estimating material properties from small motions in video
Davis, A., Bouman, K. L., Chen, J. G., Rubinstein, M., Durand, F., & Freeman, W. T. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7299171 · Cited by 132
Froth image analysis by use of transfer learning and convolutional neural networks
Fu, Y., & Aldrich, C. (2017) · Minerals Engineering · doi:10.1016/j.mineng.2017.10.005 · Cited by 132
Stojanoski, B. B., & Cusack, R. (2014) · Journal of Vision · doi:10.1167/14.12.6 · Cited by 130
Svoboda, D., Kozubek, M., & Stejskal, S. (2009) · Cytometry Part A · doi:10.1002/cyto.a.20714 · Cited by 128
Image Denoising using Gaussian Scale Mixtures in the Wavelet Domain
Portilla, J., Strela, V., Wainwright, M. J., & Simoncelli, E. P. (2002) · Cited by 128
Self-citationMorris, N., Avidan, S., Matusik, W., & Pfister, H. (2007) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2007.383003 · Cited by 127
Tight Wavelet Frames on Multislice Graphs
Leonardi, N., & Ville, D. V. D. (2013) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2013.2259825 · Cited by 126
Iterative Gaussianization: From ICA to Random Rotations
Laparra, V., Camps‐Valls, G., & Malo, J. (2011) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2011.2106511 · Cited by 125
Characterizing and Improving Stability in Neural Style Transfer
Gupta, A., Johnson, J., Alahi, A., & Fei-Fei, L. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.438 · Cited by 124
Estimating the Material Properties of Fabric from Video
Bouman, K. L., Xiao, B., Battaglia, P., & Freeman, W. T. (2013) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.455 · Cited by 123
Beyond core object recognition: Recurrent processes account for object recognition under occlusion
Rajaei, K., Mohsenzadeh, Y., Ebrahimpour, R., & Khaligh‐Razavi, S. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007001 · Cited by 123
Selectivity and tolerance for visual texture in macaque V2
Ziemba, C. M., Freeman, J., Movshon, J. A., & Simoncelli, E. P. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1510847113 · Cited by 121
Self-citationA Clustering Based Approach to Perceptual Image Hashing
Monga, V., Banerjee, A., & Evans, B. L. (2006) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2005.863502 · Cited by 121
Diamond, D. H., Heyns, P. S., & Oberholster, A. (2016) · Measurement · doi:10.1016/j.measurement.2016.10.021 · Cited by 119
Natural Images from the Birthplace of the Human Eye
Tkačik, G., Garrigan, P., Ratliff, C. P., Milčinski, G., Klein, J. M., Seyfarth, L. H., Sterling, P., Brainard, D. H., & Balasubramanian, V. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020409 · Cited by 118
Image Restoration Using Space-Variant Gaussian Scale Mixtures in Overcomplete Pyramids
Guerrero-Colon, J. A., Mancera, L., & Portilla, J. (2007) · IEEE Transactions on Image Processing · doi:10.1109/tip.2007.911473 · Cited by 118
Self-citationArtificial Intelligence for Dunhuang Cultural Heritage Protection: The Project and the Dataset
Yu, T., Lin, C., Zhang, S., Wang, C., Ding, X., An, H., Liu, X., Qu, T., Wan, L., You, S., et al. (2022) · International Journal of Computer Vision · doi:10.1007/s11263-022-01665-x · Cited by 115
Zhao, T., & Murphy, R. F. (2007) · Cytometry Part A · doi:10.1002/cyto.a.20487 · Cited by 115
No-reference image sharpness assessment based on local phase coherence measurement
Hassen, R., Wang, Z., & Salama, M. M. A. (2010) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2010.5496297 · Cited by 114
Scale-space texture description on SIFT-like textons
Xu, Y., Huang, S., Ji, H., & Fermuller, C. M. (2012) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2012.05.003 · Cited by 114
Total Variation Projection With First Order Schemes
Fadili, J. M., & Gabriel Peyré, A. (2010) · IEEE Transactions on Image Processing · doi:10.1109/tip.2010.2072512 · Cited by 114
Jacques, L., Duval, L. C., Chaux, C., & Gabriel Peyré, A. (2011) · Signal Processing · doi:10.1016/j.sigpro.2011.04.025 · Cited by 114
Inference of segmented color and texture description by tensor voting
Jia, J., & Tang, C. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.10 · Cited by 114
Primal sketch: Integrating structure and texture
Guo, C.-E., Zhu, S. C., & Wu, Y. N. (2007) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2005.09.004 · Cited by 114
Computer-aided gastrointestinal hemorrhage detection in wireless capsule endoscopy videos
Hassan, A. R., & Haque, M. A. (2015) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2015.09.005 · Cited by 113
Jana, D., & Nagarajaiah, S. (2021) · Structural Control and Health Monitoring · doi:10.1002/stc.2713 · Cited by 113
Texture design using a simplicial complex of morphable textures
Matusik, W., Zwicker, M., & Durand, F. (2005) · ACM Transactions on Graphics · doi:10.1145/1073204.1073262 · Cited by 113
Cortical Surround Interactions and Perceptual Salience via Natural Scene Statistics
Coen-Cagli, R., Dayan, P., & Schwartz, O. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002405 · Cited by 112
Contextual effects in visual working memory reveal hierarchically structured memory representations
Brady, T. F., & Alvarez, G. A. (2015) · Journal of Vision · doi:10.1167/15.15.6 · Cited by 112
Statistical modeling and conceptualization of visual patterns
Zhu, S. C. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1201820 · Cited by 110
Ashikhmin, M. (2003) · IEEE Computer Graphics and Applications · doi:10.1109/mcg.2003.1210863 · Cited by 108
Universal analytical forms for modeling image probabilities
Srivastava, A., Liu, X., & Grenander, U. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1033212 · Cited by 108
Roughness perception: A multisensory/crossmodal perspective
Stefano, N. D., & Spence, C. J. (2022) · Attention Perception & Psychophysics · doi:10.3758/s13414-022-02550-y · Cited by 107
Representation of Maximally Regular Textures in Human Visual Cortex
Kohler, P. J., Clarke, A. D. F., Yakovleva, A., Liu, Y., & Norcia, A. M. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.2962-15.2016 · Cited by 105
Development of the macaque face-patch system
Livingstone, M. S., Vincent, J. L., Arcaro, M. J., Srihasam, K., Schade, P. F., & Savage, T. (2017) · Nature Communications · doi:10.1038/ncomms14897 · Cited by 105
Greenwood, J. A., Bex, P. J., & Dakin, S. C. (2010) · Current Biology · doi:10.1016/j.cub.2010.01.023 · Cited by 105
Mid-level perceptual features distinguish objects of different real-world sizes.
Long, B., Konkle, T., Cohen, M. A., & Alvarez, G. A. (2015) · Journal of Experimental Psychology General · doi:10.1037/xge0000130 · Cited by 104
Detecting and representing predictable structure during auditory scene analysis
Sohoglu, E., & Maria Chait, A. (2016) · eLife · doi:10.7554/elife.19113 · Cited by 103
Laplacian-Steered Neural Style Transfer
Li, S., Xu, X., Nie, L., & Chua, T.-S. (2017) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3123266.3123425 · Cited by 103
Wan, L., Xiang, Y., & You, H. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2930322 · Cited by 103
Advances in Video Compression System Using Deep Neural Network: A Review and Case Studies
Ding, D., Ma, Z., Chen, D., Chen, Q., Liu, Z. S.-J., & Zhu, F. M. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2021.3059994 · Cited by 103
Lower-Level Stimulus Features Strongly Influence Responses in the Fusiform Face Area
Yue, X., Cassidy, B. S., Devaney, K. J., Holt, D. J., & Tootell, R. B. H. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhq050 · Cited by 103
Video Acceleration Magnification
Zhang, Y., Pintea, S. L., & van Gemert, J. C. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.61 · Cited by 104
Choy, S. K., & Tong, C. S. (2009) · IEEE Transactions on Image Processing · doi:10.1109/tip.2009.2033400 · Cited by 102
Prospects of Structural Similarity Index for Medical Image Analysis
Mudeng, V., Kim, M., & Choe, S.-W. (2022) · Applied Sciences · doi:10.3390/app12083754 · Cited by 101
Structure-Preserving Neural Style Transfer
Cheng, M., Liu, X.-C., Wang, J., Lu, S.-P., Lai, Y., & Rosin, P. L. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2936746 · Cited by 101
Parametric study of EEG sensitivity to phase noise during face processing
Rousselet, G. A., Pernet, C. R., Bennett, P., & Sekuler, A. B. (2008) · BMC Neuroscience · doi:10.1186/1471-2202-9-98 · Cited by 101
Merrell, P. C. (2007) · ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games (I3D) · doi:10.1145/1230100.1230119 · Cited by 101
Metadata
- Authors
- Portilla, J., & Simoncelli, E. P.
- Affiliations
- Courant Institute of Mathematical Sciences (US)
- Corresponding author
- Portilla, Javier
- Venue
- International Journal of Computer Vision
- Published
- 2000-10
- Volume
- 40
- Issue
- 1
- Pages
- 49-70
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W2127006916
- Cited by
- 1,806
- References
- 68
- Citations by year
- 2026: 55 · 2025: 75 · 2024: 70 · 2023: 67 · 2022: 81 · 2021: 92 · 2020: 91 · 2019: 94 · 2018: 101 · 2017: 101 · 2016: 100 · 2015: 86 · 2014: 83 · 2013: 70 · 2012: 61
- FWCI
- 39.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Journal of Computer Vision (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
- Keywords
- texture modeling, texture synthesis, complex wavelet transform, projection onto convex sets, natural textures
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review