7.1.4.1 Implementation of Convolution and Smoothing Techniques

Chapter Contents (Back)
Convolution. Smoothing.
See also Smoothing Techniques, Adaptive Smoothing.
See also Multi-level, Multi-Scale Segmentation and Smoothing Methods.
See also Implementation, Algorithms and Design of Filters.

Sklansky, J.,
Thresholded Convolutions Operations,
JACM(17), No. 1, January 1970, pp. 161-165. BibRef 7001

Abramatic, J.F., Faugeras, O.D.,
Sequential Convolution Techniques for Image Filtering,
ASSP(30), No. 1, 1982, pp. 1-10. BibRef 8200

Ney, H.,
A Dynamic Programming Algorithm for Nonlinear Smoothing,
SP(5), 1983, pp. 163-173. BibRef 8300

Ferrari, L.A.[Leonard A.], Sklansky, J.[Jack],
A Note on Duhamel Integrals and Running Average Filters,
CVGIP(29), No. 3, 1985, pp. 358-360.
Elsevier DOI BibRef 8500

Gourlay, A.R.,
Implicit Convolution,
IVC(3), No. 1, February 1985, pp. 15-23.
Elsevier DOI BibRef 8502

Wiejak, J.S., Buxton, H., Buxton, B.F.,
Convolution with Separable Masks for Early Image Processing,
CVGIP(32), No. 3, December 1985, pp. 279-290.
Elsevier DOI BibRef 8512

Basu, A.[Anup], Brown, C.M.[Christopher M.],
Algorithms and Hardware for Efficient Image Smoothing,
CVGIP(40), No. 2, November 1987, pp. 131-146.
Elsevier DOI BibRef 8711

O'Leary, D.P.[Dianne P.],
Some Algorithms for Approximating Convolutions,
CVGIP(41), No. 3, March 1988, pp. 333-345.
Elsevier DOI BibRef 8803

Lohar, G., Mukherjee, D.P., Dutta Majumder, D.,
On a Decomposition of 2-D Circular Convolution,
PRL(13), 1992, pp. 701-706. BibRef 9200

Glasbey, C.A., Jones, R.,
Fast Computation of Moving Average and Related Filters in Octagonal Windows,
PRL(18), No. 6, June 1997, pp. 555-565. 9710
BibRef

Cocchia, F., Carrato, S., Ramponi, G.,
Design and Real-Time Implementation of A 3-D Rational Filter for Edge-Preserving Smoothing,
Consumer(43), No. 4, November 1997, pp. 1291-1300. 9801
BibRef

Ramponi, G.,
A rational edge-preserving smoother,
ICIP95(I: 151-154).
IEEE DOI 9510
BibRef

Gorecki, C., Trolard, B.,
Optoelectronic Implementation of Adaptive Image Preprocessing Using Hybrid Modulations of Epson Liquid-Crystal Television: Applications to Smoothing and Edge Enhancement,
OptEng(37), No. 3, March 1998, pp. 924-930. 9804
BibRef

Karasik, Y.B.,
A Recursive Formula for Convolutions/Correlations and Its Application in Pattern-Recognition,
PRL(19), No. 1, January 1998, pp. 53-56. 9807
BibRef

Karasik, Y.B.,
How To Compute 3-Dimensional Convolution and/or Correlation Optically: A Mathematical Foundation,
ModOpt(45), No. 4, April 1998, pp. 817-823. 9806
BibRef
Earlier:
How to Implement N-Dimensional Image Processing Optically,
ICIP97(I: 715-718).
IEEE DOI BibRef

Boykov, Y.Y.[Yuri Y.], Veksler, O.[Olga], Zabih, R.[Ramin],
A Variable Window Approach to Early Vision,
PAMI(20), No. 12, December 1998, pp. 1283-1294.
IEEE DOI BibRef 9812
Earlier:
A Variable Neighborhood Approach to Early Vision,
DARPA97(1453-1458). Change the window at object boundaries to get better results. Apply to restoration, motion, stereo, correspondence. BibRef

Veksler, O.[Olga],
Efficient parallel optimization for potts energy with hierarchical fusion,
CVPR15(887-895)
IEEE DOI 1510
BibRef

Boykov, Y.Y.[Yuri Y.], Veksler, O.[Olga], Zabih, R.[Ramin],
Markov Random Fields with Efficient Approximations,
CVPR98(648-655).
IEEE DOI MRF Segmentation BibRef 9800

McCoy, J.S.[J. Scott],
Convolution algorithm for efficient hardware implementation,
US_Patent5,926,580, Jul 20, 1999
WWW Link. BibRef 9907

Sangwine, S.J.[Stephen J.], Ell, T.A.[Todd A.], Karasik, Y.B.,
Evaluation of 3-D Convolution by 2-D Filtering,
AppOpt(36), No. 29, 1997. BibRef 9700

Sangwine, S.J.[Stephen J.], Ell, T.A.[Todd A.],
Colour image filters based on hypercomplex convolution,
VISP(147), No. 2, April 2000, pp. 89. 0005
BibRef

Ell, T.A.[Todd A.], Sangwine, S.J.[Stephen J.],
Hypercomplex Fourier Transforms of Color Images,
IP(16), No. 1, January 2007, pp. 22-35.
IEEE DOI 0701
BibRef
Earlier: A2, A1: ICIP01(I: 137-140).
IEEE DOI 0108
BibRef

Sangwine, S.J., Ell, T.A.,
Vector zone plates as test patterns for linear vector filters,
ICIP02(II: 361-364).
IEEE DOI 0210
BibRef

Sangwine, S.J.[Stephen J.], Ell, T.A.[Todd A.],
Hypercomplex Auto- And Cross-Correlation of Color Images,
ICIP99(IV:319-322).
IEEE DOI BibRef 9900

Ell, T.A.[Todd A.],
Multi-Vector Color-Image Filters,
ICIP07(V: 245-248).
IEEE DOI 0709
BibRef
And:
Hypercomplex Color Affine Filters,
ICIP07(V: 249-252).
IEEE DOI 0709
BibRef

Ell, T.A.[Todd A.],
Hypercomplex Wiener-Khintchine Theorem with Application to Color Image Correlation,
ICIP00(Vol II: 792-795).
IEEE DOI 0008
BibRef

Evans, C., Sangwine, S.J.,
Hypercomplex Color-sensitive Smoothing Filters,
ICIP00(Vol I: 541-544).
IEEE DOI 0008
BibRef

Mount, D.M., Kanungo, T., Netanyahu, N.S., Piatko, C.D., Silverman, R., Wu, A.Y.,
Approximating large convolutions in digital images,
IP(10), No. 12, December 2001, pp. 1826-1835.
IEEE DOI 0201
BibRef
Earlier: UMD--TR4017, May 1999.
WWW Link. BibRef

Reichenbach, S.E., Geng, F.,
Two-dimensional cubic convolution,
IP(12), No. 8, August 2003, pp. 857-865.
IEEE DOI 0308
BibRef

Toivonen, T.[Tuukka], Heikkilä, J.[Janne],
Video Filtering With Fermat Number Theoretic Transforms Using Residue Number System,
CirSysVideo(16), No. 1, January 2006, pp. 92-101.
IEEE DOI 0601
Implementation of convolution filters. BibRef

Sun, C.M.[Chang-Ming],
Moving average algorithms for diamond, hexagon, and general polygonal shaped window operations,
PRL(27), No. 6, 15 April 2006, pp. 556-566.
Elsevier DOI Moving average algorithm; Diamond shaped windows; Hexagon shaped windows; Polygonal shaped windows; Local statistics 0604
BibRef

Lampert, C.H., Wirjadi, O.,
An Optimal Nonorthogonal Separation of the Anisotropic Gaussian Convolution Filter,
IP(15), No. 11, November 2006, pp. 3501-3513.
IEEE DOI 0610
BibRef

Palomares, J.M., Gonzalez, J., Ros, E., Prieto, A.,
General Logarithmic Image Processing Convolution,
IP(15), No. 11, November 2006, pp. 3602-3608.
IEEE DOI 0610
BibRef

Reju, V.G., Koh, S.N., Soon, I.Y.,
Convolution Using Discrete Sine and Cosine Transforms,
SPLetters(14), No. 7, July 2007, pp. 445-448.
IEEE DOI 0707
BibRef

Suresh, K., Sreenivas, T.V.,
Block Convolution Using Discrete Trigonometric Transforms and Discrete Fourier Transform,
SPLetters(15), No. 1, 2008, pp. 469-472.
IEEE DOI 0806
BibRef

Argyriou, V., Vlachos, T., Piroddi, R.,
Gradient-Adaptive Normalized Convolution,
SPLetters(15), No. 1, 2008, pp. 489-492.
IEEE DOI 0806
BibRef

Munoz-Barrutia, A.[Arrate], Artaechevarria, X.[Xabier], Ortiz-de-Solorzano, C.[Carlos],
Spatially Variant Convolution With Scaled B-Splines,
IP(19), No. 1, January 2010, pp. 11-24.
IEEE DOI 1001
BibRef
Earlier: A2, A1, A3:
Restoration of Biomedical Images using Locally Adaptive B-Spline Smoothing,
ICIP07(II: 425-428).
IEEE DOI 0709
BibRef

Gil, D.[Debora], Hernàndez-Sabaté, A.[Aura], Burnat, M.[Mireia], Jansen, S.[Steven], Martínez-Villalta, J.[Jordi],
Structure-Preserving Smoothing of Biomedical Images,
PR(44), No. 9, September 2011, pp. 1842-1851.
Elsevier DOI 1106
BibRef
Earlier: CAIP09(427-434).
Springer DOI 0909
Non-linear smoothing; Differential geometry; Anatomical structures segmentation; Cardiac magnetic resonance; Computerized tomography BibRef

Martinez, J., Heusdens, R., Hendriks, R.C.,
A Generalized Poisson Summation Formula and its Application to Fast Linear Convolution,
SPLetters(18), No. 9, September 2011, pp. 501-504.
IEEE DOI 1108
BibRef

Simois, F.J., Acha, J.I.,
A New Algorithm for Real Data Convolutions With j -Circulants,
SPLetters(18), No. 11, November 2011, pp. 655-658.
IEEE DOI 1112
BibRef

Milanfar, P.[Peyman],
Symmetrizing Smoothing Filters,
SIIMS(6), No. 1, 2013, pp. 263-284.
DOI Link 1304
BibRef

Wei, J.N.[Jia-Ning], Bouman, C.A., Allebach, J.P.,
Fast Space-Varying Convolution Using Matrix Source Coding With Applications to Camera Stray Light Reduction,
IP(23), No. 5, May 2014, pp. 1965-1979.
IEEE DOI 1405
convolution BibRef

Huo, H.[Haiye],
A new convolution theorem associated with the linear canonical transform,
SIViP(13), No. 1, February 2019, pp. 127-133.
Springer DOI 1901
BibRef

Aguilar-González, A.[Abiel], Arias-Estrada, M.[Miguel], Pérez-Patricio, M.[Madaín], Camas-Anzueto, J.L.,
An FPGA 2D-convolution unit based on the CAPH language,
RealTimeIP(16), No. 2, April 2019, pp. 305-319.
Springer DOI 1904
BibRef

Chun, I.Y.[Il Yong], Hong, D.[David], Adcock, B.[Ben], Fessler, J.A.[Jeffrey A.],
Convolutional Analysis Operator Learning: Dependence on Training Data,
SPLetters(26), No. 8, August 2019, pp. 1137-1141.
IEEE DOI 1908
convolution, probability, unsupervised learning, convolutional analysis operator learning, training data, CAOL, dependence on training sample size BibRef

Ramasinghe, S.[Sameera], Khan, S.H.[Salman H.], Barnes, N.[Nick], Gould, S.[Stephen],
Representation Learning on Unit Ball with 3D Roto-translational Equivariance,
IJCV(128), No. 6, June 2020, pp. 1612-1634.
Springer DOI 2006
BibRef
And:
Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes,
WACV20(21-31)
IEEE DOI 2006
Shape, Convolution, Kernel, Feature extraction, Solid modeling Volumetric convolution. BibRef

Rahman, S.[Shafin], Khan, S.H.[Salman H.], Barnes, N.[Nick], Khan, F.S.[Fahad Shahbaz],
Any-shot Object Detection,
ACCV20(III:89-106).
Springer DOI 2103
BibRef

Roddy, P.J., McEwen, J.D.,
Sifting Convolution on the Sphere,
SPLetters(28), 2021, pp. 304-308.
IEEE DOI 2102
Convolution, Harmonic analysis, Kernel, Standards, Transforms, Hilbert space, Convolution, 2-sphere, spherical harmonics BibRef

Xiao, Y.Q.[You-Qing], Cai, Z.C.[Zhan-Chuan], Yuan, X.[Xixi],
YuvConv: Multi-Scale Non-Uniform Convolution Structure Based on YUV Color Model,
MultMed(23), 2021, pp. 2533-2544.
IEEE DOI 2108
Tensile stress, Convolution, Machine learning, Spatial resolution, Computational modeling, Task analysis, Feature extraction, YuvConv, WideResnet BibRef


Arizumi, N.,
Piecewise Polynomial Approximation Method for Convolution With Large Kernel,
ICIP20(3080-3083)
IEEE DOI 2011
Kernel, Convolution, Image processing, Cameras, Real-time systems, Robots, Splines (mathematics), high-resolution image, convolution, faster computation BibRef

Nguyen, A.D., Choi, S., Kim, W., Lee, S., Lin, W.,
Statistical Convolution On Unordered Point Set,
ICIP20(3468-3472)
IEEE DOI 2011
Feature extraction, Convolution, Task analysis, Computer architecture, Neural networks, Shape, Deep Learning BibRef

Carranza, C., Llamocca, D., Pattichis, M.,
Fast and Scalable 2D Convolutions and Cross-correlations for Processing Image Databases and Videos on CPUs,
SSIAI20(70-73)
IEEE DOI 2009
convolutional neural nets, fast Fourier transforms, input-output programs, microprocessor chips, optimisation BibRef

Sekikawa, Y.[Yusuke], Ishikawa, K.[Kohta], Hara, K.[Kosuke], Yoshida, Y.[Yuuichi], Suzuki, K.[Koichiro], Sato, I.[Ikuro], Saito, H.[Hideo],
Constant Velocity 3D Convolution,
3DV18(343-351)
IEEE DOI 1812
approximation theory, cameras, convolution, distance measurement, feature extraction, image representation, image sequences, Fourier transform BibRef

Wang, H.[Hui], Wang, Y.[Yue], Cao, J.J.[Jun-Jie], Liu, X.P.[Xiu-Ping],
Structure-Preserving Texture Smoothing via Adaptive Patches,
PSIVTWS17(311-324).
Springer DOI 1806
BibRef

Szegedy, C.[Christian], Liu, W.[Wei], Jia, Y.Q.[Yang-Qing], Sermanet, P.[Pierre], Reed, S.[Scott], Anguelov, D.[Dragomir], Erhan, D.[Dumitru], Vanhoucke, V.[Vincent], Rabinovich, A.[Andrew],
Going deeper with convolutions,
CVPR15(1-9)
IEEE DOI 1510
BibRef

Yoshizawa, S.[Shin], Yokota, H.[Hideo],
Fast L1 Gaussian convolution via domain splitting,
ICIP14(2908-2912)
IEEE DOI 1502
Approximation algorithms BibRef

Fanello, S.R.[Sean Ryan], Keskin, C.[Cem], Kohli, P.[Pushmeet], Izadi, S.[Shahram], Shotton, J.[Jamie], Criminisi, A.[Antonio], Pattacini, U.[Ugo], Paek, T.[Tim],
Filter Forests for Learning Data-Dependent Convolutional Kernels,
CVPR14(1709-1716)
IEEE DOI 1409
Decision Trees BibRef

Jackett, C.J., Ollington, R., Lovell, J.L.,
Efficient Digital FFT Convolution with Boundary Kernel Renormalisation,
DICTA13(1-6)
IEEE DOI 1402
convolution BibRef

Iandola, F.N.[Forrest N.], Sheffield, D.[David], Anderson, M.J.[Michael J.], Phothilimthana, P.M.[Phitchaya Mangpo], Keutzer, K.[Kurt],
Communication-minimizing 2D convolution in GPU registers,
ICIP13(2116-2120)
IEEE DOI 1402
Convolution;GPU;autotuning;parallel BibRef

Boldyš, J.[Jirí], Flusser, J.[Jan],
Invariants to Symmetrical Convolution with Application to Dihedral Kernel Symmetry,
CIAP13(II:369-378).
Springer DOI 1309
BibRef

Gonzalez, D.[Damien], Malgouyres, R.[Rémy], Esbelin, H.A.[Henri-Alex], Samir, C.[Chafik],
Convergence of Level-Wise Convolution Differential Estimators,
DGCI13(335-346).
Springer DOI 1304
BibRef
Earlier:
Fast Level-Wise Convolution,
IWCIA12(223-233).
Springer DOI 1211
BibRef

Wesierski, D.[Daniel], Mkhinini, M.[Maher], Horain, P.[Patrick], Jezierska, A.[Anna],
Fast recursive ensemble convolution of Haar-like features,
CVPR12(3689-3696).
IEEE DOI 1208
BibRef

Albanese, G.[Giulia], Cipolla, M.[Marco], Valenti, C.[Cesare],
Genetic Normalized Convolution,
CIAP11(I: 670-679).
Springer DOI 1109
BibRef

Svoboda, D.[David],
Efficient Computation of Convolution of Huge Images,
CIAP11(I: 453-462).
Springer DOI 1109
BibRef

Hu, X.[Xin], Peng, H.[Hui], Kesker, J.[Joseph], Cai, X.[Xiang], Wee, W.G.[William G.], Lee, J.H.[Jing-Huei],
An Improved Adaptive Smoothing Method,
CIAP09(757-766).
Springer DOI 0909
BibRef

Belt, H.J.W.,
Word length reduction for the integral image,
ICIP08(805-808).
IEEE DOI 0810
Sums of areas. BibRef

Knutsson, H.[Hans], Westin, C.F.[Carl-Fredrik], Andersson, M.[Mats],
Representing Local Structure Using Tensors II,
SCIA11(545-556).
Springer DOI 1105
BibRef

Brun, A., Westin, C.F., Haker, S., Knutsson, H.,
A Tensor-Like Representation for Averaging, Filtering and Interpolation of 3-D Object Orientation Data,
ICIP05(III: 1092-1095).
IEEE DOI 0512
BibRef

Lumsdaine, A., Wyatt, Jr., J.L., Elfadel, I.M.,
Nonlinear Analog Networks for Image Smoothing and Segmentation,
MIT AI Memo-1280, January 1991. BibRef 9101

Deriche, R., Cocquerez, J.P., Almouzny, G.,
An efficient method to build early image description,
ICPR88(I: 588-590).
IEEE DOI 8811
BibRef

Pan, F.[Feng], Gu, W.K.[Wei-Kang], Jin, R.J.[Ren-Jie], Yao, Q.D.[Qin-Dong],
One-pass preprocessing algorithm for real-time image processing system,
ICPR88(II: 851-853).
IEEE DOI 8811
BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Fourier Descriptors, DFT, FFT Computation, Use, Frequency Analysis .


Last update:Oct 16, 2021 at 11:54:21