7.10.9 Autoregressive Texture Models, AR Models

Chapter Contents (Back)
Autoregression. Autoregressive Measures.

de Souza, P.[Peter],
Texture Recognition via Autoregression,
PR(15), No. 6, 1982, pp. 471-475.
Elsevier DOI BibRef 8200

Mital, D.P., Leng, G.W.,
An Autoregressive Approach to Texture Analysis,
PRAI(8), 1994, pp. 845-857. BibRef 9400

Tekalp, A.M., Kaufman, H., Woods, J.W.,
Fast Recursive Estimation of the Parameters of a Space-Varying Autoregressive Image Model,
ASSP(33), 1985, pp. 469-472. BibRef 8500

Lawton, W.M.,
A Complete Spectral Characterization of Quarter-Plane Autoregressive Models,
ASSP(33), 1985, pp. 1617-1619. BibRef 8500

Yemez, Y., Anarim, E., Istefanopulos, Y.,
Causal and semicausal AR image model identification using the EM algorithm,
IP(2), No. 4, October 1993, pp. 523-528.
IEEE DOI 0402
BibRef

Sarkar, A., Sharma, K.M.S., Sonak, R.V.,
A New Approach for Subset 2-D AR Model Identification for Describing Textures,
IP(6), No. 3, March 1997, pp. 407-413.
IEEE DOI 9703
BibRef

Zheng, W.X.,
Estimations of Autoregressive Signals from Noisy Measurements,
VISP(144), No. 1, February 1997, pp. 39-45. 9706
BibRef

Kadaba, S.R., Gelfand, S.B., Kashyap, R.L.,
Recursive Estimation of Images Using Non-gaussian Autoregressive Models,
IP(7), No. 10, October 1998, pp. 1439-1452.
IEEE DOI BibRef 9810

Bennett, J.W.[Jesse W.], Khotanzad, A.[Alireza],
Maximum Likelihood Estimation Methods for Multispectral Random Field Image Models,
PAMI(21), No. 6, June 1999, pp. 537-543.
IEEE DOI BibRef 9906
Earlier:
A Maximum Likelihood Estimation Method for Multispectral Autoregressive Image Models,
ICIP97(II: 839-842).
IEEE DOI
See also Multispectral Random Field Models for Synthesis and Analysis of Color Images. BibRef

Eom, K.B.[Kie B.],
Generalized circular autoregressive models for isotropic and anisotropic Gaussian textures,
JOSA-A(18), No. 8, August 2001, pp. 1822-1831.
WWW Link. Synthesize textures. 0109
BibRef
Earlier:
Generalized Circular Autoregressive Models for Modeling Isotropic and Anisotropic Textures,
ICIP01(II: 129-132).
IEEE DOI 0108
BibRef

Penny, W.D., Roberts, S.J.,
Bayesian multivariate autoregressive models with structured priors,
VISP(149), No. 1, February 2002, pp. 33-41.
IEEE Top Reference. 0205
BibRef

Woerdeman, H.J.[Hugo J.], Geronimo, J.S.[Jeffrey S.], Castro, G.[Glaysar],
A numerical algorithm for stable 2D autoregressive filter design,
SP(83), No. 6, June 2003, pp. 1299-1308.
Elsevier DOI 0304
BibRef

Alata, O.[Olivier], Olivier, C.[Christian],
Choice of a 2-D causal autoregressive texture model using information criteria,
PRL(24), No. 9-10, June 2003, pp. 1191-1201.
Elsevier DOI 0304
BibRef

Alata, O.[Olivier], Ramananjarasoa, C.[Clarisse],
Unsupervised textured image segmentation using 2-D quarter plane autoregressive model with four prediction supports,
PRL(26), No. 8, June 2005, pp. 1069-1081.
Elsevier DOI 0506
BibRef

Alata, O.[Olivier], Cariou, C., Ramananjarasoa, C.[Clarisse], Najim, M.,
Classification of rotated and scaled textures using HMHV spectrum estimation and the Fourier-Mellin transform,
ICIP98(I: 53-56).
IEEE DOI 9810
BibRef

Alata, O., Baylou, P., Najim, M.,
Multiple resolution image segmentation using four QP supports of 2D autoregressive model,
ICIP96(I: 277-280).
IEEE DOI 9610
BibRef

Serban, I., Turcu, F., Najim, M.,
A Fast 2-D AR Parameter Estimation Algorithm Based on Functional Schur Coefficients,
SPLetters(16), No. 12, December 2009, pp. 1039-1042.
IEEE DOI 0909
BibRef

Hasan, M.K.[M. Kamrul], Apu, M.S.[M. Shakib], Molla, M.K.I.[M. Khademul Islam],
A robust method for parameter estimation of AR systems using empirical mode decomposition,
SIViP(4), No. 4, November 2010, pp. 451-461.
WWW Link. 1101
BibRef

Nelson, J.D.B.,
Fused Lasso and rotation invariant autoregressive models for texture classification,
PRL(34), No. 16, 2013, pp. 2166-2172.
Elsevier DOI 1310
Texture classification BibRef

Ghirmai, T.,
Representing a Cascade of Complex Gaussian AR Models by a Single Laplace AR Model,
SPLetters(22), No. 1, January 2015, pp. 110-114.
IEEE DOI 1410
Gaussian processes BibRef

Toyoura, M.[Masahiro], Aruga, H.[Haruhito], Turk, M.[Matthew], Mao, X.Y.[Xiao-Yang],
Mono-spectrum marker: an AR marker robust to image blur and defocus,
VC(30), No. 9, September 2014, pp. 1035-1044.
WWW Link. 1410
BibRef

Boulemnadjel, A., Hachouf, F., Kharfouchi, S.,
GMM Estimation of 2D-RCA Models With Applications to Texture Image Classification,
IP(25), No. 2, February 2016, pp. 528-539.
IEEE DOI 1601
Analytical models 2D indexed random coefficients autoregressive model. BibRef

Mehmood, A.[Ammara], Aslam, M.S.[Muhammad Saeed], Chaudhary, N.I.[Naveed Ishtiaq], Zameer, A.[Aneela], Raja, M.A.Z.[Muhammad Asif Zahoor],
Parameter estimation for Hammerstein control autoregressive systems using differential evolution,
SIViP(12), No. 8, November 2018, pp. 1603-1610.
Springer DOI 1809
BibRef

Luo, Q.[Qing], Griffith, D.A.[Daniel A.], Wu, H.Y.[Hua-Yi],
On the Statistical Distribution of the Nonzero Spatial Autocorrelation Parameter in a Simultaneous Autoregressive Model,
IJGI(7), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Liu, P.[Peng], Chen, L.[Lei], Zhang, H.[Haopeng], Zhang, Y.X.[Yun-Xiang], Liu, C.[Chao], Li, C.[Cheng], Wang, Z.H.[Zhi-Hui],
PEAR: Positional-encoded Asynchronous Autoregression for satellite anomaly detection,
PRL(176), 2023, pp. 96-101.
Elsevier DOI 2312
Satellite data, Anomaly detection, Autoregressive model, Positional encoding BibRef


Lu, J.[Jiasen], Clark, C.[Christopher], Lee, S.H.[Sang-Ho], Zhang, Z.C.[Zi-Chen], Khosla, S.[Savya], Marten, R.[Ryan], Hoiem, D.[Derek], Kembhavi, A.[Aniruddha],
Unified-IO 2: Scaling Autoregressive Multimodal Models with Vision, Language, Audio, and Action,
CVPR24(26429-26445)
IEEE DOI 2410
Training, Image synthesis, Computational modeling, Semantics, Benchmark testing, Transformers, Data models BibRef

Piergiovanni, A.J., Noble, I.[Isaac], Kim, D.[Dahun], Ryoo, M.S.[Michael S.], Gomes, V.[Victor], Angelova, A.[Anelia],
Mirasol3B: A Multimodal Autoregressive Model for Time-Aligned and Contextual Modalities,
CVPR24(26794-26804)
IEEE DOI 2410
Computational modeling, Media, Benchmark testing, Synchronization, Context modeling BibRef

Kakogeorgiou, I.[Ioannis], Gidaris, S.[Spyros], Karantzalos, K.[Konstantinos], Komodakis, N.[Nikos],
SPOT: Self-Training with Patch-Order Permutation for Object-Centric Learning with Autoregressive Transformers,
CVPR24(22776-22786)
IEEE DOI Code:
WWW Link. 2410
Training, Costs, Object segmentation, Transformers, Vectors, Decoding, object-centric learning, autoregressive transformer, spot BibRef

Tai, J.Y.[Jin-Yang],
Global Perception Based Autoregressive Neural Processes,
ICCV23(10453-10463)
IEEE DOI 2401
BibRef

Li, S.J.[Shu-Jia], Wang, D.Z.[De-Zhao], Fan, Z.[Zejia], Liu, J.Y.[Jia-Ying],
Content-Adaptive Parallel Entropy Coding for End-to-End Image Compression,
ICIP23(3195-3199)
IEEE DOI 2312
BibRef

Mahajan, S.[Shweta], Roth, S.[Stefan],
PixelPyramids: Exact Inference Models from Lossless Image Pyramids,
ICCV21(6619-6628)
IEEE DOI 2203
Computational modeling, Estimation, Computational efficiency, Neural generative models, Image and video synthesis, Machine learning architectures and formulations BibRef

Bourquard, A.[Aurelien], Kirshner, H.[Hagai], Unser, M.[Michael],
Resolution-invariant separable ARMA modeling of images,
ICIP11(1833-1836).
IEEE DOI 1201
Stochastic modelling independent of resolution. BibRef

Feldmann, C.[Christian], Balle, J.[Johannes],
Improved entropy coding for component-based image coding,
ICIP11(325-328).
IEEE DOI 1201
BibRef

Balle, J.[Johannes], Jurczyk, B.[Bastian], Stojanovic, A.[Aleksandar],
Component-based image coding using non-local means filtering and an autoregressive texture model,
ICIP09(1937-1940).
IEEE DOI 0911
BibRef

Abbadeni, N.[Noureddine],
Texture Representation and Retrieval Using the Causal Autoregressive Model,
JVCIR(21), No. 7, October 2010, pp. 651-664.
Elsevier DOI 1003
BibRef
Earlier: Visual07(559-569).
Springer DOI 0706
BibRef
Earlier:
Perceptual Meaning of the Estimated Parameters of the Autoregressive Model,
ICIP05(III: 1164-1167).
IEEE DOI 0512
Texture Representation; Autoregressive model; Causality; Estimated parameters; Perceptual meaning; Texture Retrieval; CBIR; Precision/recall BibRef

Abbadeni, N.[Noureddine],
Computational Perceptual Features for Texture Representation and Retrieval,
IP(20), No. 1, January 2011, pp. 236-246.
IEEE DOI 1101
BibRef

Abbadeni, N.[Noureddine],
Texture Retrieval Effectiveness Improvement Using Multiple Representations Fusion,
PSIVT09(485-496).
Springer DOI 0901
BibRef
Earlier:
An Approach Based on Multiple Representations and Multiple Queries for Invariant Image Retrieval,
Visual07(570-579).
Springer DOI 0706
BibRef

Abbadeni, N.[Noureddine], Ziou, D.[Djemel], Wang, S.R.[Sheng-Rui],
Autocovariance-based Perceptual Textural Features Corresponding to Human Visual Perception,
ICPR00(Vol III: 901-904).
IEEE DOI 0009
BibRef

Abbadeni, N., Ziou, D., Wang, S.,
Computational Measures Corresponding to Perceptual Textural Features,
ICIP00(Vol III: 897-900).
IEEE DOI 0008
BibRef

Abbadeni, N.[Noureddine], Alhichri, H.S.[Haikel S.], Elmasry, A.B.[Alaa B.],
Tackling the Problem of Invariant Texture Retrieval Using Multiple Strategies,
IJIG(11), No. 1, January 2011, pp. 43-64.
DOI Link 1103
BibRef

Wan, J., Mao, J., Wang, C.D.,
Multiresolution Rotation Invariant Simultaneous Auto Regressive Model for Texture Analysis,
ICPR88(II: 845-847).
IEEE DOI BibRef 8800

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Autocorrelation Texture Models .


Last update:Nov 26, 2024 at 16:40:19