Gerritsen, F.A.,
Aardema, L.G.,
Design and use of DIP-1: A fast, flexible and dynamically
microprogrammable pipelined image processor,
PR(14), No. 1-6, 1981, pp. 319-330.
Elsevier DOI
0309
BibRef
Carlson, C.R.[Curtis R.],
Arbeiter, J.H.[James H.],
Bessler, R.F.[Roger F.],
Real-time hierarchal pyramid signal processing apparatus,
US_Patent4,674,125, Jun 16, 1987
WWW Link.
BibRef
8706
Bessler, R.F.[Roger F.],
Arbeiter, J.H.[James H.],
Sinniger, J.O.[Joseph O.],
Multiplexed real-time pyramid signal processing system,
US_Patent4,709,394, Nov 24, 1987
WWW Link. Burt pyramid implementation
BibRef
8711
van der Wal, G.S.[Gooitzen S.],
Sinniger, J.O.[Joseph O.],
Anderson, C.H.[Charles H.],
Implementation architecture for performing hierarchical motion analysis
of video images in real time,
US_Patent5,276,513, Jan 4, 1994
WWW Link.
BibRef
9401
Andrews, B.A.[Barry A.],
Vector image processing system,
US_Patent4,742,552, May 3, 1988
WWW Link.
BibRef
8805
Abbot, L.,
Haralick, R.M.,
Zhuang, X.,
Pipeline Architectures for Morphologic Image Analysis,
MVA(1), 1988, pp. 23-40.
BibRef
8800
Sanz, J.L.C., and
Dinstein, I.,
Projection-Based Geometric Feature Extraction for Computer Vision:
Algorithms in Pipeline Architectures,
PAMI(9), No. 1, January 1987, pp. 160-168.
Similar to CVPR85 paper.
Exploring how the projection can be used for some real computations,
and how to do them fast. (There is another paper on projection
processing somewhere.)
BibRef
8701
Sanz, J.L.C.[Jorge L.C.],
Hinkle, E.B.[Eric B.], and
Dinstein, I.[Its'hak],
Computing Geometrical Features of Digital Objects in General
Purpose Image Processing Pipeline Architectures,
CVPR85(265-270).
IBM San Jose.
Algorithms designed for current pipeline systems. Shows the results
for the computation of the projection of an image.
BibRef
8500
Gennery, D.B., and
Wilcox, B.,
A Pipelined Processor for Low-Level Vision,
CVPR85(608-613).
JPL. System being build for actual processing of data. Basic design
is standard.
BibRef
8500
Persoon, E.,
A Pipelined Image Analysis System Using Custom Integrated Circuits,
PAMI(10), No. 1, January 1988, pp. 110-116.
IEEE DOI
BibRef
8801
Jonker, P.P.,
Komen, E.R.,
Kraaijveld, M.A.,
A Scalable, Real-Time, Image-Processing Pipeline,
MVA(8), No. 2, 1995, pp. 110-121.
BibRef
9500
Earlier: A1, A2 only:
ICPR92(IV:142-146).
IEEE DOI
9208
BibRef
McLauchlan, P.F.,
Reid, I.D.,
Fairley, S.M.,
Murray, D.W.,
The Pipe-Group Architecture Real Time Active Vision,
RealTimeImg(3), No. 5, October 1997, pp. 319-330.
HTML Version.
9712
BibRef
Siyal, M.Y.,
Fathi, M.,
Atiquzzaman, M.,
A Parallel Pipeline Based Multiprocessor System for Real-Time
Measurement of Road Traffic Parameters,
RealTimeImg(6), No. 3, June 2000, pp. 241-249.
0008
BibRef
Fleury, M.,
Downton, A.C.,
Clark, A.F.,
Pipelined parallelisation of automatic face inspection,
MVA(12), No. 4, 2000, pp. 203-211.
Springer DOI
0101
BibRef
Wu, C.W.,
Bit-level pipelined 2-D digital filters for real-time image processing,
CirSysVideo(1), No. 1, March 1991, pp. 22-34.
IEEE Top Reference.
0206
BibRef
Lu, T.,
Azimi-Sadjadi, M.R.,
Interleaved pipeline structures for two-dimensional recursive filtering,
CirSysVideo(3), No. 1, February 1993, pp. 87-91.
IEEE Top Reference.
0206
BibRef
Gray, III, D.M.[Donald M.],
Needle, D.L.[David L.],
Digital signal processor architecture,
US_Patent5,752,073, May 12, 1998
WWW Link.
BibRef
9805
Singh, S.[Sameer],
Singh, M.[Maneesha],
On the optimality of image processing pipeline,
PR(37), No. 4, April 2004, pp. 707-724.
Elsevier DOI
0403
BibRef
Kumaki, T.[Takeshi],
Kuroda, Y.[Yasuto],
Ishizaki, M.[Masakatsu],
Koide, T.[Tetsushi],
Mattausch, H.J.[Hans Jürgen],
Noda, H.[Hideyuki],
Dosaka, K.[Katsumi],
Arimoto, K.[Kazutami],
Saito, K.[Kazunori],
Real-Time Huffman Encoder with Pipelined CAM-Based Data Path and
Code-Word-Table Optimizer,
IEICE(E90-D), No. 1, January 2007, pp. 334-345.
DOI Link
0701
BibRef
Seetharaman, G.,
Venkataramani, B.,
Lakshminarayanan, G.,
Automation techniques for implementation of hybrid wave-pipelined 2D
DWT,
RealTimeIP(3), No. 3, September 2008, pp. xx-yy.
Springer DOI
0804
BibRef
Dokladal, P.[Petr],
Dokladalova, E.[Eva],
Computationally efficient, one-pass algorithm for morphological filters,
JVCIR(22), No. 5, July 2011, pp. 411-420.
Elsevier DOI
1106
Mathematical morphology; Serial filters; Nonlinear filters; Real-time
implementation; Streaming; Algorithm
BibRef
Bartovsky, J.[Jan],
Dokladalova, E.[Eva],
Dokladal, P.[Petr],
Georgiev, V.[Vjaceslav],
Pipeline architecture for compound morphological operators,
ICIP10(3765-3768).
IEEE DOI
1009
BibRef
Acosta, E.[Eric],
Liu, A.[Alan],
A pipeline virtual environment architecture for multicore processor
systems,
VC(27), No. 11, November 2011, pp. 1099-1114.
WWW Link.
1210
BibRef
Jian, G.A.[Guo-An],
Chien, C.A.[Cheng-An],
Chen, P.S.[Peng-Sheng],
Guo, J.I.[Jiun-In],
A Verification-Aware Design Methodology for Thread Pipelining
Parallelization,
IEICE(E95-D), No. 10, October 2012, pp. 2505-2513.
WWW Link.
1210
BibRef
Déforges, O.[Olivier],
Normand, N.[Nicolas],
Babel, M.[Marie],
Fast recursive grayscale morphology operators:
From the algorithm to the pipeline architecture,
RealTimeIP(8), No. 2, June 2013, pp. 143-152.
WWW Link.
1306
BibRef
Zhang, B.,
Zhao, C.,
Mei, K.,
Zhao, J.,
Zheng, N.,
Hierarchical and Parallel Pipelined Heterogeneous SoC for Embedded
Vision Processing,
CirSysVideo(28), No. 6, June 2018, pp. 1434-1444.
IEEE DOI
1806
Algorithm design and analysis, Computer architecture, Estimation,
Hardware, Machine vision,
system on chip (SoC)
BibRef
Mestiri, H.,
Kahri, F.,
Bedoui, M.,
Bouallegue, B.,
Machhout, M.,
High throughput pipelined hardware implementation of the KECCAK hash
function,
ISIVC16(282-286)
IEEE DOI
1704
Algorithm design and analysis
BibRef
Helala, M.A.[Mohamed A.],
Qureshi, F.Z.[Faisal Z.],
Accelerating Cost Volume Filtering Using Salient Subvolumes and Robust
Occlusion Handling,
ACCV14(II: 316-331).
Springer DOI
1504
pixel labeling.
BibRef
Helala, M.A.[Mohamed A.],
Pu, K.Q.[Ken Q.],
Qureshi, F.Z.[Faisal Z.],
Towards Efficient Feedback Control in Streaming Computer Vision
Pipelines,
UCCV14(314-329).
Springer DOI
1504
BibRef
And:
A Stream Algebra for Computer Vision Pipelines,
WebScale14(800-807)
IEEE DOI
1409
Computer Vision Pipelines
BibRef
Li, W.W.[Wei-Wei],
Li, H.T.[Hai-Tao],
Gu, H.[Haiyan],
Study of Remote Sensing Imagery Parallel Segmentation Based on Block
and Processing Chain Strategy,
ISIDF11(1-4).
IEEE DOI
1111
BibRef
Ferretti, M.,
Boffadossi, M.,
A parallel pipelined implementation of LOCO-I for JPEG-LS,
ICPR04(I: 769-772).
IEEE DOI
0409
BibRef
Sawchuk, A.A.,
Optical Signal and Image Processing:
From Analog Systems to Digital Pipeline Smart Pixels,
ICIP98(I: 478).
IEEE DOI
9810
BibRef
Kameda, Y.,
Taoda, T.,
Minoh, M.,
High Speed 3d Reconstruction by Video Image Pipeline Processing
and Division of Spatio-temporal Space,
MVA98(xx-yy).
BibRef
9800
Gray, C.T.,
Liu, W.,
Hughes, T.,
Cavin, R.,
Chen, S.S.,
P3A: a partitionable parallel/pipeline architecture for real-time image
processing,
ICPR90(II: 529-531).
IEEE DOI
9208
BibRef
Deguchi, K.,
Tago, K.,
Morishita, I.,
Integrated parallel image processings on a pipelined MIMD
multi-processor system PSM,
ICPR90(II: 442-444).
IEEE DOI
9208
BibRef
Abdelguerfi, M.,
Sood, A.K.,
Khalaf, S.,
Parallel bit-level pipelined VLSI processing unit for the histogramming
operation,
CVPR88(945-950).
IEEE DOI
0403
BibRef
Khan, I.,
Implementation of Conditional Processing and Pyramids
with a General Purpose Pipelined Pixel Processor,
CVPR86(288-292).
Seems to be an enhanced pipeline (2 parallel? processors in it)?
BibRef
8600
Chapter on Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection continues in
Array Processors, Massive Parallel Systems, Pyramids .