A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients

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

Motion microscopy for visualizing and quantifying small motions

Wadhwa, N., Chen, J. G., Sellon, J. B., Wei, D., Rubinstein, M., Ghaffari, R., Freeman, D. M., Büyüköztürk, O., Wang, P., Sun, S., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1703715114 · Cited by 100

Geometric Feature Extraction by a Multimarked Point Process

Lafarge, F., Gimel’farb, G., & Descombes, X. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2009.152 · Cited by 99

Unsupervised learning predicts human perception and misperception of gloss

Storrs, K. R., Anderson, B. L., & Fleming, R. W. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01097-6 · Cited by 98

Structural Approaches to Image Quality Assessment

Wang, Z., Bovik, A. C., & Simoncelli, E. P. (2005) · Elsevier eBooks · doi:10.1016/b978-012119792-6/50119-4 · Cited by 98

Oriented Correlation Models of Distorted Natural Images With Application to Natural Stereopair Quality Evaluation

Su, C.-C., Cormack, L. K., & Bovik, A. C. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2409558 · Cited by 97

Skeleton-Aided Articulated Motion Generation

Yan, Y., Xu, J., Ni, B., Zhang, W., & Yang, X. (2017) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3123266.3123277 · Cited by 97

Texture synthesis and perception: Using computational models to study texture representations in the human visual system

Balas, B. (2005) · Vision Research · doi:10.1016/j.visres.2005.04.013 · Cited by 96

Bridges between multiple-point geostatistics and texture synthesis: Review and guidelines for future research

Mariethoz, G., & Lefèbvre, S. (2014) · Computers & Geosciences · doi:10.1016/j.cageo.2014.01.001 · Cited by 95

Neural responses to natural and model-matched stimuli reveal distinct computations in primary and nonprimary auditory cortex

Norman-Haignere, S., & McDermott, J. H. (2018) · PLoS Biology · doi:10.1371/journal.pbio.2005127 · Cited by 95

The dynamics of pattern matching in camouflaging cuttlefish

Woo, T., Liang, X., Evans, D. A., Fernandez, O., Kretschmer, F., Reiter, S., & Laurent, G. (2023) · Nature · doi:10.1038/s41586-023-06259-2 · Cited by 95

Inverse texture synthesis

Wei, L., Han, J., Zhou, K., Bao, H., Guo, B., & Shum, H. (2008) · ACM Transactions on Graphics · doi:10.1145/1360612.1360651 · Cited by 94

Statistical Modeling of Photographic Images

Simoncelli, E. P. (2005) · Handbook of Image and Video Processing · doi:10.1016/b978-012119792-6/50089-9 · Cited by 93

Wavelet based co-occurrence histogram features for texture classification with an application to script identification in a document image

Hiremath, P. S., & Shivashankar, S. (2008) · Pattern Recognition Letters · doi:10.1016/j.patrec.2008.01.012 · Cited by 92

Seeing the Arrow of Time

Pickup, L., Zheng, P., Wei, D., Shih, Y., Zhang, C., Zisserman, A., Schölkopf, B., & Freeman, W. T. (2014) · 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.2014.262 · Cited by 92

Steerable Pyramids and Tight Wavelet Frames in $L_{2}({\BBR}^{d})$

Unser, M. A., Chenouard, N., & Ville, D. V. D. (2011) · IEEE Transactions on Image Processing · doi:10.1109/tip.2011.2138147 · Cited by 90

A review of cuttlefish camouflage and object recognition and evidence for depth perception

Kelman, E. J., Osorio, D., & Baddeley, R. (2008) · Journal of Experimental Biology · doi:10.1242/jeb.015149 · Cited by 89

Structural features of pyrocarbon atomistic models constructed from transmission electron microscopy images

Leyssale, J., da Costa, J., Germain, C., Weisbecker, P., & Vignoles, G. L. (2012) · Carbon · doi:10.1016/j.carbon.2012.05.015 · Cited by 89

Pooling of continuous features provides a unifying account of crowding

Keshvari, S., & Rosenholtz, R. E. (2016) · Journal of Vision · doi:10.1167/16.3.39 · Cited by 89

Stimulus- and goal-oriented frameworks for understanding natural vision

Turner, M. H., Giraldo, L. G. S., Schwartz, O., & Rieke, F. M. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0284-0 · Cited by 88

What you see is what you expect: rapid scene understanding benefits from prior experience

Greene, M. R., Botros, A. P., Beck, D. M., & Fei-Fei, L. (2015) · Attention Perception & Psychophysics · doi:10.3758/s13414-015-0859-8 · Cited by 88

Multiscale texture synthesis

Han, C., Risser, E., Ramamoorthi, R., & Grinspun, E. (2008) · ACM Transactions on Graphics · doi:10.1145/1360612.1360650 · Cited by 88

Motion recognition using nonparametric image motion models estimated from temporal and multiscale co-occurrence statistics

Fablet, R., & Bouthémy, P. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1251155 · Cited by 88

Global ensemble texture representations are critical to rapid scene perception.

Brady, T. F., Shafer-Skelton, A., & Alvarez, G. A. (2017) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/xhp0000399 · Cited by 87

Perception of visual texture and the expression of disruptive camouflage by the cuttlefish,Sepia officinalis

Kelman, E. J., Baddeley, R., Shohet, A. J., & Osorio, D. (2007) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2007.0240 · Cited by 87

Nonaccidental Properties Underlie Human Categorization of Complex Natural Scenes

Walther, D. B., & Shen, D. (2014) · Psychological Science · doi:10.1177/0956797613512662 · Cited by 86

Visual Vibrometry: Estimating Material Properties from Small Motions in Video

Davis, A., Bouman, K. L., Chen, J. G., Rubinstein, M., Büyüköztürk, O., Durand, F., & Freeman, W. T. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2622271 · Cited by 85

Estimating perception of scene layout properties from global image features

Ross, M. G., & Oliva, A. (2010) · Journal of Vision · doi:10.1167/10.1.2 · Cited by 85

Reduced-Reference Quality Assessment Based on the Entropy of DWT Coefficients of Locally Weighted Gradient Magnitudes

Golestaneh, S. A., & Karam, L. J. (2016) · IEEE Transactions on Image Processing · doi:10.1109/tip.2016.2601821 · Cited by 85

Hybrid Texture Synthesis

Nealen, A., & Alexa, M. (2003) · TUbilio (Technical University of Darmstadt) · Cited by 85

Local statistics in natural scenes predict the saliency of synthetic textures

Tkačik, G., Prentice, J., Victor, J. D., & Balasubramanian, V. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0914916107 · Cited by 84

Texture and art with deep neural networks

Gatys, L. A., Ecker, A. S., & Bethge, M. (2017) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.08.019 · Cited by 83

Visual Functions of Primate Area V4

Pasupathy, A., Popovkina, D. V., & Kim, T. (2020) · Annual Review of Vision Science · doi:10.1146/annurev-vision-030320-041306 · Cited by 83

Generative modelling of BRDF textures from flash images

Henzler, P., Deschaintre, V., Mitra, N. J., & Ritschel, T. (2021) · ACM Transactions on Graphics · doi:10.1145/3478513.3480507 · Cited by 83

Learning to Perceive Transparency from the Statistics of Natural Scenes

Levin, A., Zomet, A., & Weiss, Y. (2002) · Cited by 83

The Promise and Perils of Near-Regular Texture

Liu, Y., Tsin, Y., & Lin, W. (2004) · International Journal of Computer Vision · doi:10.1007/s11263-005-4639-0 · Cited by 82

A statistical model for synthesis of detailed facial geometry

Golovinskiy, A., Matusik, W., Pfister, H., Rusinkiewicz, S. M., & Funkhouser, T. A. (2006) · ACM Transactions on Graphics · doi:10.1145/1141911.1141988 · Cited by 82

IoT-based smart city development using big data analytical approach

Rathore, M. M., Ahmad, A., & Paul, A. (2016) · IEEE International Conference on Automatica · doi:10.1109/ica-acca.2016.7778510 · Cited by 81

Target-free 3D tiny structural vibration measurement based on deep learning and motion magnification

Shao, Y., Li, L., Li, J., An, S., & Hao, H. (2022) · Journal of Sound and Vibration · doi:10.1016/j.jsv.2022.117244 · Cited by 81

Perception of edges and visual texture in the camouflage of the common cuttlefish, Sepia officinalis

Zylinski, S., Osorio, D., & Shohet, A. J. (2008) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2008.0264 · Cited by 80

Example-based synthesis of stylized facial animations

Fišer, J., Jamriška, O., Simons, D., Shechtman, E., Lu, J., Asente, P., Lukáč, M., & Sýkora, D. (2017) · ACM Transactions on Graphics · doi:10.1145/3072959.3073660 · Cited by 79

A Biologically Motivated Multiresolution Approach to Contour Detection

Pápari, G., Campisi, P., Petkov, N., & Neri, A. (2007) · EURASIP Journal on Advances in Signal Processing · doi:10.1155/2007/71828 · Cited by 79

Rotation-invariant texture retrieval with gaussianized steerable pyramids

Tzagkarakis, G., Beferull‐Lozano, B., & Tsakalides, P. (2006) · IEEE Transactions on Image Processing · doi:10.1109/tip.2006.877356 · Cited by 79

A Novel Depth-Based Virtual View Synthesis Method for Free Viewpoint Video

Ahn, I., & Kim, C. (2013) · IEEE Transactions on Broadcasting · doi:10.1109/tbc.2013.2281658 · Cited by 79

Awesome Typography: Statistics-Based Text Effects Transfer

Yang, S., Liu, J., Lian, Z., & Guo, Z. (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.2017.308 · Cited by 79

A Unifying Parametric Framework for 2D Steerable Wavelet Transforms

Unser, M. A., & Chenouard, N. (2013) · SIAM Journal on Imaging Sciences · doi:10.1137/120866014 · Cited by 78

TileGAN

Frühstück, A., Alhashim, I., & Wonka, P. (2019) · ACM Transactions on Graphics · doi:10.1145/3306346.3322993 · Cited by 78

Challenges to pooling models of crowding: Implications for visual mechanisms

Rosenholtz, R. E., Yu, D., & Keshvari, S. (2019) · Journal of Vision · doi:10.1167/19.7.15 · Cited by 78

Super-resolving Noisy Images

Singh, A., Porikli, F., & Ahuja, N. (2014) · 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.2014.364 · Cited by 77

Image upsampling via texture hallucination

HaCohen, Y., Fattal, R., & Lischinski, D. (2010) · IEEE International Conference on Computational Photography (ICCP) · doi:10.1109/iccphot.2010.5585097 · Cited by 77

Stroke Pattern Analysis and Synthesis

Barla, P., Breslav, S., Thollot, J., Sillion, F. X., & Markosian, L. (2006) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2006.00986.x · Cited by 77

A Parametric Framework for Video Compression Using Region-Based Texture Models

Zhang, F., & Bull, D. (2011) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2011.2165201 · Cited by 77

Balanced Increases in Selectivity and Tolerance Produce Constant Sparseness along the Ventral Visual Stream

Rust, N. C., & DiCarlo, J. J. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.6125-11.2012 · Cited by 77

Association Between Changes in Mammographic Image Features and Risk for Near-Term Breast Cancer Development

Tan, M., Zheng, B., Leader, J. K., & Gur, D. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2527619 · Cited by 77

Neural Mechanisms of Material Perception: Quest on Shitsukan

Komatsu, H., & Goda, N. (2018) · Neuroscience · doi:10.1016/j.neuroscience.2018.09.001 · Cited by 76

Fault segmentation in fabric images using Gabor wavelet transform

Arivazhagan, S., Ganesan, L., & Bama, S. S. (2006) · Machine Vision and Applications · doi:10.1007/s00138-005-0007-x · Cited by 76

Reference-free detection of minute, non-visible, damage using full-field, high-resolution mode shapes output-only identified from digital videos of structures

Yang, Y., Dorn, C. J., Mancini, T., Talken, Z., Theiler, J. P., Kenyon, G. T., Farrar, C. R., & Mascareñas, D. (2017) · Structural Health Monitoring · doi:10.1177/1475921717704385 · Cited by 76

Texture-like representation of objects in human visual cortex

Jagadeesh, A. V., & Gardner, J. L. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2115302119 · Cited by 75

Nanoscale structure and texture of highly anisotropic pyrocarbons revisited with transmission electron microscopy, image processing, neutron diffraction and atomistic modeling

Farbos, B., Weisbecker, P., Fischer, H. E., da Costa, J., Lalanne, M., Chollon, G., Germain, C., Vignoles, G. L., & Leyssale, J. (2014) · Carbon · doi:10.1016/j.carbon.2014.08.087 · Cited by 75

Fusion of Global and Local Descriptors for Remote Sensing Image Classification

Risojević, V., & Babić, Z. (2012) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2012.2225596 · Cited by 75

A spectral histogram model for texton modeling and texture discrimination

Liu, X., & Wang, D. (2002) · Vision Research · doi:10.1016/s0042-6989(02)00297-3 · Cited by 75

Adaptive and Selective Time Averaging of Auditory Scenes

McWalter, R., & McDermott, J. H. (2018) · Current Biology · doi:10.1016/j.cub.2018.03.049 · Cited by 74

Image Recovery Via Hybrid Sparse Representations: A Deterministic Annealing Approach

Li, X. (2011) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2011.2138676 · Cited by 73

Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances

Moser, B. B., Raue, F., Frolov, S., Palacio, S., Hees, J., & Dengel, A. R. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2023.3243794 · Cited by 73

Texture Analysis and Segmentation Using Modulation Features, Generative Models, and Weighted Curve Evolution

Kokkinos, I., Evangelopoulos, G., & Maragos, P. (2008) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.33 · Cited by 72

A study of relative phase in complex wavelet domain: Property, statistics and applications in texture image retrieval and segmentation

Vo, A., & Oraintara, S. (2009) · Signal Processing Image Communication · doi:10.1016/j.image.2009.09.003 · Cited by 72

Convolution Neural Networks With Two Pathways for Image Style Recognition

Sun, T., Wang, Y., Yang, J. J., & Hu, X. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2710631 · Cited by 72

Modeling Visual Patterns by Integrating Descriptive and Generative Methods

Guo, C.-E., Zhu, S. C., & Wu, Y. N. (2003) · International Journal of Computer Vision · doi:10.1023/a:1023023207396 · Cited by 72

Unsupervised image translation

Resales, Achan, & Frey (2003) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2003.1238384 · Cited by 72

Representations in mental imagery and working memory: Evidence from different types of visual masks

Borst, G., Ganis, G., Thompson, W. L., & Kosslyn, S. M. (2011) · Memory & Cognition · doi:10.3758/s13421-011-0143-7 · Cited by 71

High-dimensional representation of texture in somatosensory cortex of primates

Lieber, J. D., & Bensmaı̈a, S. J. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1818501116 · Cited by 71

What your visual system sees where you are not looking

Rosenholtz, R. E. (2011) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.876659 · Cited by 70

Efficient Texture Image Retrieval Using Copulas in a Bayesian Framework

Kwitt, R., Meerwald, P., & Uhl, A. (2011) · IEEE Transactions on Image Processing · doi:10.1109/tip.2011.2108663 · Cited by 70

Graphcut Textures: Image and Video Synthesis Using Graph Cuts

Kwatra, V., Schödl, A., Essa, I. A., Turk, G., & Bobick, A. (2023) · ACM eBooks · doi:10.1145/3596711.3596773 · Cited by 69

Texture synthesis for 3D shape representation

Gorla, G., Interrante, V. L., & Sapiro, G. (2003) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2003.1260745 · Cited by 69

Natural versus Synthetic Stimuli for Estimating Receptive Field Models: A Comparison of Predictive Robustness

Talebi, V., & Baker, C. L. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.4661-12.2012 · Cited by 68

Representation of the Material Properties of Objects in the Visual Cortex of Nonhuman Primates

Goda, N., Tachibana, A., Okazawa, G., & Komatsu, H. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.2593-13.2014 · Cited by 68

Quantitative Evaluation of Near Regular Texture Synthesis Algorithms

Lin, W., Hays, J. H., Wu, C., Liu, Y., & Kwatra, V. (2006) · 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.2006.233 · Cited by 68

How Sensitive Is the Human Visual System to the Local Statistics of Natural Images?

Gerhard, H. E., Wichmann, F. A., & Bethge, M. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002873 · Cited by 67

Perceptual Annotation: Measuring Human Vision to Improve Computer Vision

Scheirer, W. J., Anthony, S. E., Nakayama, K., & Cox, D. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.2297711 · Cited by 67

VISIBLE: Video-Assisted Keystroke Inference from Tablet Backside Motion

Sun, J., Jin, X., Chen, Y., Zhang, J., Zhang, R., & Zhang, Y. (2016) · Network and Distributed System Security Symposium · doi:10.14722/ndss.2016.23060 · Cited by 67

A parametric texture model based on deep convolutional features closely matches texture appearance for humans

Wallis, T. S. A., Funke, C. M., Ecker, A. S., Gatys, L. A., Wichmann, F. A., & Bethge, M. (2017) · Journal of Vision · doi:10.1167/17.12.5 · Cited by 67

Development of a Gray-Level Co-Occurrence Matrix-Based Texture Orientation Estimation Method and Its Application in Sea Surface Wind Direction Retrieval From SAR Imagery

Zheng, G., Li, X., Zhou, L., Yang, J., Ren, L., Chen, P., Zhang, H., & Lou, X. (2018) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2018.2812778 · Cited by 67

Harnessing natural textures for multivariate visualization

Interrante, V. L. (2000) · IEEE Computer Graphics and Applications · doi:10.1109/mcg.2000.888001 · Cited by 67

The role of higher order image statistics in masking scene gist recognition

Loschky, L. C., Hansen, B. C., Sethi, A., & Pydimarri, T. N. (2010) · Attention Perception & Psychophysics · doi:10.3758/app.72.2.427 · Cited by 66

Link the remote sensing big data to the image features via wavelet transformation

Wang, L., Song, W., & Liu, P. (2016) · Cluster Computing · doi:10.1007/s10586-016-0569-6 · Cited by 66

In the light of feature distributions: moment matching for Neural Style Transfer

Kalischek, N., Wegner, J. D., & Konrad Schindler, B. (2021) · 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/cvpr46437.2021.00926 · Cited by 66

Quantum mechanics in computer vision: Automatic object extraction

Aytekin, Ç., Serkan Kiranyaz, B., & Gabbouj, M. (2013) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2013.6738513 · Cited by 66

Structural similarity metrics for texture analysis and retrieval

Zujovic, J., Pappas, T. N., & Neuhoff, D. L. (2009) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2009.5413897 · Cited by 66

Texture Synthesis with Grouplets

Gabriel Peyré, A. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2009.54 · Cited by 66

Multi- spectral image resolution refinement using stationary wavelet transform

Beaulieu, M., Foucher, S., & Gagnon, L. (2004) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2003.1295352 · Cited by 65

Monitoring of mineral processing systems by using textural image analysis

Kistner, M., Jemwa, G. T., & Aldrich, C. (2013) · Minerals Engineering · doi:10.1016/j.mineng.2013.05.022 · Cited by 65

Gradual Development of Visual Texture-Selective Properties Between Macaque Areas V2 and V4

Okazawa, G., Tajima, S., & Komatsu, H. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw282 · Cited by 65

Phase-based displacement measurement on a straight edge using an optimal complex Gabor filter

Miao, Y., Jeon, J. Y., Kong, Y., & Park, G. (2021) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2021.108224 · Cited by 64

Computer vision‐based real‐time cable tension estimation algorithm using complexity pursuit from video and its application in Fred‐Hartman cable‐stayed bridge

Jana, D., Nagarajaiah, S., & Yang, Y. (2022) · Structural Control and Health Monitoring · doi:10.1002/stc.2985 · Cited by 65

Unsupervised Texture Segmentation with Nonparametric Neighborhood Statistics

Awate, S. P., Taşdizen, T., & Whitaker, R. (2006) · Lecture notes in computer science · doi:10.1007/11744047_38 · Cited by 64

Statistical correlates of perceived gloss in natural images

Wiebel, C. B., Toscani, M., & Gegenfurtner, K. R. (2015) · Vision Research · doi:10.1016/j.visres.2015.04.010 · Cited by 63

Texture synthesis and nonparametric resampling of random fields

Levina, E., & Bickel, P. J. (2006) · The Annals of Statistics · doi:10.1214/009053606000000588 · Cited by 63

Texture Classification Using Sparse Frame-Based Representations

Skretting, K., & Husøy, J. H. (2006) · EURASIP Journal on Advances in Signal Processing · doi:10.1155/asp/2006/52561 · Cited by 63

Image content is more important than Bouma’s Law for scene metamers

Wallis, T. S. A., Funke, C. M., Ecker, A. S., Gatys, L. A., Wichmann, F. A., & Bethge, M. (2019) · eLife · doi:10.7554/elife.42512 · Cited by 63

Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics ProgramsPreprint

Mansinghka, V. K., Kulkarni, T. D., Perov, Y., & Tenenbaum, J. B. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1307.0060 · Cited by 63

Texture Modeling and Synthesis using Joint Statistics of Complex Wavelet Coefficients

Portilla, J., & Simoncelli, E. P. (1999)

Texture characterization via joint statistics of wavelet coefficient magnitudes

Simoncelli, E. P., & Portilla, J. (2002) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.1998.723417 · Cited by 180

Texture Representation and Synthesis Using Correlation of Complex Wavelet Coefficient Magnitudes

Portilla, J., & Simoncelli, E. P. (1999) · Cited by 7

Texture synthesis via projection onto multiscale, multilayer statisticsPreprint

He, J., & Hirn, M. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.10825 · Cited by 2

DWT based non-parametric texture modeling

Menegaz, G. (2002) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2001.958981 · Cited by 5