Professor II

Anne H Schistad Solberg

Publications

  • 87 publications found
Vedal, Amund Hansen; Eikvil, Line; Solberg, Anne H Schistad; Salberg, Arnt Børre and Malde, Ketil. (2026).
Hierarchical classification and embedding quality of plankton. Visual Intelligence
Visual Intelligence Days. 22. september 2026. Quality Hotel Gardermoen.
NVA Poster
Show summary
Poster
Jenssen, Robert; Eikvil, Line; Solberg, Anne H Schistad; Solheim, Inger and Bjørklund, Petter. (2026).
Visual Intelligence Annual Report 2025.
UiT Norges arktiske universitet. 1. april 2026.
NVA Full text Report basic
Jenssen, Robert; Eikvil, Line; Solberg, Anne H Schistad; Solheim, Inger and Bjørklund, Petter. (2025).
Visual Intelligence Annual Report 2024.
UiT Norges arktiske universitet. 1. april 2025.
NVA Full text Report basic
Show summary
The Visual Intelligence Annual Report 2024 highlights the centre's progress, activities and achieved innovations for 2022. It describes new deep learning methods which address pressing societal needs in the fields of medicine and health, marine science, the energy sector, and earth observation.
Jenssen, Robert; Eikvil, Line; Solberg, Anne H Schistad; Solheim, Inger and Bjørklund, Petter. (2024).
Visual Intelligence Annual Report 2023.
UiT Norges arktiske universitet. 1. april 2024.
NVA Full text Report basic
Aasan, Marius; Kolbjørnsen, Odd; Solberg, Anne H Schistad and Rivera, Adín Ramírez. (2024).
A Spitting Image: Modular Superpixel Tokenization in Vision Transformers. CVF/ECCV
CVF/ECCV More Exploration. Less Exploitation (MELEX) Workshop. 29. september – 4. october 2024. Milano.
NVA Scientific lecture
Aasan, Marius; Kolbjørnsen, Odd; Solberg, Anne H Schistad and Rivera, Adín Ramírez. (2024).
A Spitting Image: Modular Tokenization in Vision Transformers. SFI Visual Intelligence
Visual Intelligence Days. 24–25. september 2024. Oslo Gardermoen.
NVA Poster
Aasan, Marius; Kolbjørnsen, Odd; Solberg, Anne H Schistad and Rivera, Adín Ramírez. (2024).
A Spitting Image: Modular Superpixel Tokenization in Vision Transformers. CVF/ECCV
CVF/ECCV More Exploration. Less Exploitation (MELEX) Workshop. 29. september – 4. october 2024. Milano.
NVA Scientific lecture
Jenssen, Robert; Eikvil, Line; Solberg, Anne H Schistad and Solheim, Inger. (2023).
Visual Intelligence Annual Report 2022.
UiT Norges arktiske universitet. 1. april 2023.
NVA Full text Report basic
Jenssen, Robert; Eikvil, Line; Solberg, Anne H Schistad and Solheim, Inger. (2022).
Visual Intelligence Annual Report 2021.
UiT Norges arktiske universitet. 1. april 2022.
NVA Full text Report basic
Show summary
The Visual Intelligence Annual Report 2021 highlights the centre's progress, activities and achieved innovations for 2021. It describes new deep learning methods which address pressing societal needs in the fields of medicine and health, marine science, the energy sector, and earth observation.
Jenssen, Robert; Eikvil, Line; Solberg, Anne H Schistad and Solheim, Inger. (2021).
Visual Intelligence Annual Report 2020.
UiT Norges arktiske universitet. 1. april 2021.
NVA Full text Report basic
Show summary
The Visual Intelligence Annual Report 2020 highlights the centre's progress, activities and achieved innovations for 2020. It describes new deep learning methods which address pressing societal needs in the fields of medicine and health, marine science, the energy sector, and earth observation.
Jenssen, Robert; Solberg, Anne H Schistad and Eikvil, Line. (2021).
Norge er verdensledende på bildeanalyse med kunstig intelligens.
21. june 2021.
NVA Interview
Salberg, Arnt Børre; Rudjord, Øystein and Solberg, Anne H Schistad. (2014).
Oil spill detection in hybrid-polarimetric SAR images.
IEEE Transactions on Geoscience and Remote Sensing. ISSN 0196-2892 1558-0644. Vol. 52. Issue 10. S. 6521-6533.
DOI NVA Academic article
Show summary
Oil spill detection in SAR images operating in a hybrid-polarimetric mode is examined. We propose and review several strategies for oil spill detection in hybrid-polarimetric SAR data. The retrieved measures are successfully applied to SAR data covering oil spill experiments outside Norway and the Deepwater Horizon incident in the Gulf of Mexico. It is shown that, under the assumption of a two-scale Bragg scattering model, a coherence measure may be recovered equally well from hybrid-polarimetric data, as for full-polarimetric data, and that this measure may be retrieved directly from the measurements without the need for any additional assumptions. The results show that low-wind lookalikes may be suppressed at the same time as the contrast of the oil spills is maintained using hybrid-polarimetric data and that multifeature images may be constructed to further enhance the oil spill detection performance. Due to the potential of wide swath widths, we conclude that hybrid-polarity is an attractive mode for future SAR-based oil spill monitoring.
Salberg, Arnt Børre; Longépé, Nicolas; Hansen, Morten Wergeland; Rudjord, Øystein; Larsen, Siri Øyen; Solberg, Anne H Schistad; Zortea, Maciel and Mouche, Alexis A.. (2013).
Report SAR analysis and comparisons - EU FP-7 project SeaU, Deliverable 12.1.
Research Executive Agency - European Commission. 94 S.
NVA Report
Salberg, Arnt Børre; Rudjord, Øystein and Solberg, Anne H Schistad. (2012).
Model based oil spill detection using polarimetric SAR.
IEEE Press. Geoscience and Remote Sensing Symposium (IGARSS). 2012 IEEE International. ISBN 9781467311601. S. 5884-5887.
DOI NVA Academic chapter/conference paper
Show summary
In this paper we propose a model-based oil spill detection approach using polarimetic SAR data. The underlying hypothesis is that the co-polarized phase difference is zero when assuming Bragg scattering mechanisms. From this hypothesis we may construct a (linear) model and derive features that discriminates oil slicks from sea water using dual-polarized (VV and HH) SAR data. We also investigate the model when assuming X-Bragg scattering, and derive a feature based on the Pauli decomposition that are invariant to the tilt angle reflection plane. The oil spill detection methodology is evaluated on a Radarsat-2 quad-pol image that covers various types of oil released in an oil-in-sea exercise in Norway. The results show that the oil spills are clearly visible in all of the derived feature-based images. Furthermore, the feature images have a more homogeneous background than the VV-polarized SAR image, in particular the Pauli-based feature image that suppresses a non-oil slick present in the VV-image.
Salberg, Arnt Børre; Rudjord, Øystein and Solberg, Anne H S. (2012).
Oil spill detection in compact polarimetry SAR images. ESA
SeaSAR-2012. 18–22. june 2012. Tromsø.
NVA Scientific lecture
Salberg, Arnt Børre; Rudjord, Øystein and Solberg, Anne H Schistad. (2012).
Model based oil spill detection using polarimetric SAR.
IEEE Geoscience and Remote Sensing Letters. ISSN 1545-598X 1558-0571. S. 5884-5887.
DOI NVA Academic article
Solberg, Anne H S and Trier, Øivind Thorvald Due. (2011).
Radarsat-2 oil spill detection. Performance study 2010.
Norsk Regnesentral. SAMBA/47/11. 19 S.
NVA Report
Salberg, Arnt-Børre; Solberg, Svein; Solberg, Anne H. Schistad and Lange, Holger. (2009).
Leaf Area Index Estimation from Land Cover Classification Based on Hyperspectral Data.
Norsk Regnesentral. SAMBA/52/09. 20 S. 15. december 2009.
NVA Report
Solberg, Anne H. Schistad and Trier, Øivind Thorvald Due. (2009).
SatHavOlje. Improvements during the 2008 project.
Norsk Regnesentral. SAMBA/01/09. 31 S. 9. october 2009.
NVA Report
Solberg, Anne H. Schistad. (2008).
Confidence Estimation - Report for SatHav Olje.
Norsk Regnesentral. SAMBA/09/08. 39 S. 1. february 2008.
NVA Report
Huseby, Ragnar Bang and Solberg, Anne H. Schistad. (2008).
Statistical analysis of oil spill data.
Norsk Regnesentral. SAMBA/05/08. 28. february 2008.
NVA Report
Solberg, Anne Helene Schistad; Brekke, C and Husøy, Per Ove. (2007).
Oil spill detection in Radarsat and Envisat SAR images.
IEEE Transactions on Geoscience and Remote Sensing. ISSN 0196-2892 1558-0644. Vol. 45.
DOI NVA Academic article
Show summary
We present algorithms for automatic detection of oil spills in synthetic aperture radar (SAR) images. The algorithms consist of three main parts, namely: 1) detection of dark spots; 2) feature extraction from the dark spot candidates; and 3) classification of dark spots as oil spills or look-alikes. The algorithms have been trained on a large number of Radarsat and Envisat Advanced Synthetic Aperture Radar (ASAR) images. The performance of the algorithm is compared to manual and semiautomatic approaches in a benchmark study using 59 Radarsat and Envisat images. The algorithms can be considered to be a good alternative to manual inspection when large ocean areas are to be inspected
Brekke, Camilla and Solberg, Anne H. Schistad. (2006).
Classification methods for oil spill detection by SAR imaging.
SPIE Conference: Image and Signal Processing for Remote Sensing. 1. september 2006.
NVA Scientific lecture
Solberg, Anne H. Schistad. (2006).
Data fusion for remote sensing applications, in Signal and Image Processing for Remote Sensing (ed. C. H. Chen).
Taylor and Francis Books. 24 S. 10. september 2006.
NVA Non-fiction book
Storvik, Geir Olve; Fjørtoft, Roger Sverre and Solberg, Anne H S. (2005).
A Bayesian approach to classification of multi-scale remote sensing data.
IEEE Transactions on Geoscience and Remote Sensing. ISSN 0196-2892 1558-0644. Vol. 43. Issue 3. S. 539-547.
DOI NVA Academic article
Show summary
Several earth observation satellites acquire image bands with different spatial resolutions, e.g., a panchromatic band with high resolution and spectral bands with lower resolution. Likewise, we often face the problem of different resolutions when performing joint analysis of images acquired by different satellites. This work presents models and methods for classification of multiresolution images. The approach is based on the concept of a reference resolution, corresponding to the highest resolution in the dataset. Prior knowledge about the spatial characteristics of the classes is specified through a Markov random field model at the reference resolution. Data at coarser scales are modeled as mixed pixels by relating the observations to the classes at the reference resolution. A Bayesian framework for classification based on this multiscale model is proposed. The classification is realized by an iterative conditional modes (ICM) algorithm. The parameter estimation can be based both on a training set and on pixels with unknown class. A computationally efficient scheme based on a combination of the ICM and the expectation-maximization algorithm is proposed. Results obtained on simulated and real satellite images are presented.
Aurdal, Lars; Huseby, Ragnar Bang; Eikvil, Line; Solberg, Rune; Schuler, Dagrun Vikhamar and Solberg, Anne H Schistad. (2005).
Use of hidden Markov models and phenology for multitemporal satellite image classification: applications to mountain vegetation classification.
IEEE (Institute of Electrical and Electronics Engineers). Proceedings of the 2005 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images. Biloxi. Mississippi. USA. 16-18 May 2005. ISBN 9780780391185. S. 220-224.
DOI NVA Academic chapter/conference paper
Huseby, Ragnar Bang; Aurdal, Lars; Eikvil, Line; Solberg, Rune; Schuler, Dagrun Vikhamar and Solberg, Anne H Schistad. (2005).
Alignment of growth seasons from satellite data.
IEEE (Institute of Electrical and Electronics Engineers). Proceedings of the 2005 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images. Biloxi. Mississippi. USA. 16-18 May 2005. ISBN 9780780391185. S. 213-216.
DOI NVA Academic chapter/conference paper
Solberg, Anne H S; Brekke, Camilla; Solberg, Rune and Husøy, Per Ove. (2004).
Algorithms for oil spill detection in Radarsat and ENVISAT SAR images. IEEE
IEEE International Geoscience and Remote Sensing Symposium. 20–24. september 2004. Anchorage. Alaska.
NVA Scientific lecture
Solberg, Anne H S; Dokken, Sverre Thune and Solberg, Rune. (2003).
Automatic detection of oil spills in ENVISAT, Radarsat and ERS SAR images. IEEE
IGARSS03. 21–25. july 2003. Toulouse.
NVA Poster
Storvik, Geir Olve; Fjørtoft, Roger Sverre and Solberg, Anne H S. (2003).
Parameter estimation and classification of multi-scale remote sensing data.
International Geoscience and Remote Sensing Symposium (IGARSS'03). 21–25. july 2003. Toulouse.
NVA Scientific lecture
Solberg, Anne H S; Storvik, Geir Olve and Fjørtoft, Roger Sverre. (2002).
A Comparison of Criteria for Decision Fusion and Parameter Estimation in Statistical Multisensor Image Classification.
International Geoscience and Remote Sensing Symposium (IGARSS 02). 1. june 2002. Toronto.
NVA Scientific lecture
Storvik, Geir Olve; Fjørtoft, Roger and Solberg, Anne H S. (2002).
Integration of multisource image data at different resolutions and time points. A mathematical framework for EOtools.
Norsk Regnesentral. 36 S.
NVA Report
Fjørtoft, Roger Sverre; Solberg, Anne H S and Storvik, Geir Olve. (2002).
A new approach to statistical multisensor image classification.
IGARSS'02. 24–28. june 2002. Toronto.
NVA Scientific lecture
Amlien, Jostein and Solberg, Anne H. Schistad. (2001).
Methods for retrieval of forest parameters from satellite remote sensing.
Norsk Regnesentral. SAMBA/26/01. 29 S. 1. december 2001.
NVA Report
Solberg, Anne H S; Storvik, Geir Olve; Solberg, Rune and Volden, Espen. (1999).
Automatic detection of oil spills in ERS SAR images.
IEEE Transactions on Geoscience and Remote Sensing. ISSN 0196-2892 1558-0644. Vol. 37. Issue 4. S. 1916-1924.
DOI NVA Academic article
Show summary
We present algorithms for the automatic detection of oil spills in SAR images. The developed framework consists of first detecting dark spots in the image, then computing a set of features for each dark spot, before the spot is classified as either an oil slick or a ''lookalike'' (other oceanographic phenomena which resemble oil slicks), The classification rule is constructed by combining statistical modeling with a rule-based approach. Prior knowledge about the higher probability for the presence of oil slicks around ships and oil platforms is incorporated into the model, In addition, knowledge about the external conditions like mind level and slick surroundings are taken into account. The presented algorithms are tested on 84 SAR images. The algorithm can discriminate between oil slicks and lookalikes with high accuracy. 94% of the oil slicks and 99% of the lookalikes mere correctly classified.
Solberg, Anne H. Schistad. (1999).
Contextual data fusion applied to forest map revision.
IEEE Transactions on Geoscience and Remote Sensing. ISSN 0196-2892 1558-0644. Vol. 37. Issue 3. S. 1234-1243. 1. january 1999.
NVA Academic article
Eikvil, Line; Holden, Marit and Solberg, Anne H. Schistad. (1999).
Seismic Attribute Analysis, Part IV.
Norsk Regnesentral. SAMBA/17/99. 76 S. 1. november 1999.
NVA Report
Solberg, Anne H. Schistad and Solberg, Rune. (1999).
SAR interferometry - A survey.
938. ISBN 9788253904214. 32 S. 1. march 1999.
NVA Report
Holden, Marit; Solberg, Anne H. Schistad and Solberg, Rune. (1998).
Wet snow-cover mapping by C- and L-band polarimetric SAR.
Ukjent. S. 1533-1537. 6. july 1998.
NVA Academic article
Holden, Marit; Solberg, Anne H. Schistad and Solberg, Rune. (1998).
Wet snow-cover mapping by C- and L-band polarimtric SAR.
Ukjent. 18. june 1998.
NVA Academic article
Volden, Espen; Solberg, Anne H. Schistad and Huseby, Ragnar Bang. (1998).
Forest classification using spectrometer and SAR data.
Ukjent.
NVA Academic article
Holden, Marit; Solberg, Anne H. Schistad and Solberg, Rune. (1998).
Snow mapping by multifrequency polarimetric SAR - An investigation of EMISAR data from the EMAC'95 snow campaign in Norway.
934. ISBN 9788253904177. 1. december 1998.
NVA Report
Solberg, Anne H. Schistad; Holden, Marit; Storvik, Geir; Teigland, André and Møller-Holst, Johan. (1998).
Seismic image analysis: 3D texture attributes and classification - part III.
Norsk Regnesentral. SAMBA/21/98. 1. december 1998.
NVA Report
Volden, Espen; Solberg, Anne H. Schistad; Huseby, Ragnar Bang and Solberg, Rune. (1998).
Forest mapping my airborne remote sensing techniques.
928. ISBN 9788253904481. 43 S. 1. june 1998.
NVA Report
Solberg, Anne H S; Storvik, Geir Olve; Teigland, André; Møller-Holst, Johan; Berge, Anker M. and Abrahamsen, Petter. (1997).
Seismic image analysis: A pilot study for investigating the relevance of using image analysis techniques on seismic data.
Norsk Regnesentral. BILD/06/97. -1 S.
NVA Report
Aas, Kjersti; Solberg, Anne H. Schistad; Koren, Hans and Solberg, Rune. (1997).
Semi-automatic revision of forest maps combining spectral, textural, laser altimeter and GIS data.
Ukjent. 1. january 1997.
NVA Academic article
Solberg, Anne H. Schistad and Jain, Anil K.. (1997).
Texture analysis of SAR images: a comparative study.
IEEE Transactions on Geoscience and Remote Sensing. ISSN 0196-2892 1558-0644. Vol. 35. Issue 1.
NVA Full text Academic article
Solberg, Anne H. Schistad; Volden, Espen and Storvik, Geir. (1997).
Slick signature screening: Algorithm improvement.
Norsk Regnesentral. BILD/04/97. 55 S. 1. april 1997.
NVA Report
Solberg, Anne H. Schistad and Volden, Espen. (1997).
Incorporation of prior knowledge in automatic classification of oil spills in ERS SAR images.
Ukjent. S. 157-159. 1. august 1997.
NVA Academic article
Holden, Marit; Solberg, Anne H. Schistad; Storvik, Geir; Teigland, André; Møller-Holst, Johan and Berge, Anker M.. (1997).
Seismic image analysis: 3D texture attributes and classification - part II.
Norsk Regnesentral. BILD/07/97. 60 S. 1. december 1997.
NVA Report
Solberg, Anne H. Schistad; Taxt, Torfinn and Jain, Anil K.. (1996).
A Markov random field model for classification of multisource satellite imagery.
IEEE Transactions on Geoscience and Remote Sensing. ISSN 0196-2892 1558-0644. Vol. 34. Issue 1. S. 100-113. 1. january 1996.
DOI NVA Full text Academic article
Aas, Kjersti; Solberg, Anne H. Schistad; Koren, Hans and Solberg, Rune. (1996).
Semi-automatic revision of forest maps combining spectral, textural, laser altimeter and GIS data.
Ukjent. 10. june 1996.
NVA Academic article
Solberg, Rune; Solberg, Anne H. Schistad and Koren, Hans. (1996).
Forest classification - problem formulation and initial experiments.
Norsk Regnesentral. BILD/03/96. 44 S. 1. february 1996.
NVA Full text Report
Show summary
The focus of the research presented in this report is the challenge of computer-based forest classification of digitized infrared aerial photography. Interpretation of such demanding imagery has until now exclusively been performed manually. the current research is a first step in the direction of the goal of semi-automatic interpretation of forest imagery. The first objective of the work presented has been to identify and define the problems of forest mapping in an as concise may as possible and in terms of a remote sensing approach. The second objective has been to do initial data exploration and testes of standard image analysis methods. It has been determined that the geometrical distortions in an aerial photography will heavily influence the performance of automatic classification if the effects are not modelled and corrected. The discrimination experiments show that both texture and spectral features to some extent may be used to discriminate tree species and cutting classes. In data with low geometrical distortion, some GLCM textural features showed good discrimination ability. Based on the distribution of a set of ten derived spectral classes, we can discriminate properly between (i) spruce, cutting class 1; (ii) spruce and pine, cutting class 3; (iii) spruce, cutting classes 4-5; and (iv) deciduous forest.
Aas, Kjersti; Solberg, Anne H. Schistad; Koren, Hans and Solberg, Rune. (1996).
Semi-automatic revision of forest maps combining spectral, texture, laser altimeter and GIS data.
Norsk Regnesentral. 909. ISBN 9788253904085. 76 S. 1. october 1996.
NVA Report
Solberg, Anne H. Schistad. (1996).
Multisource classification of remotely sensed imagery.
Ukjent. 10. june 1996.
NVA Academic article
Solberg, Rune and Solberg, Anne H. Schistad. (1996).
ENVISYS user requirements.
EN 1009 D1. 142 S. 1. june 1996.
NVA Report
Solberg, Rune; Solberg, Anne H. Schistad; Koren, Hans and Aas, Kjersti. (1996).
The suitability of future high-resolution satellite imagery for forest inventory.
Ukjent. 27. may 1996.
NVA Academic article
Solberg, Anne H. Schistad and Solberg, Rune. (1996).
Algorithms for semi-automatic detection of oil spills in ERS SAR imagery.
Norsk Regnesentral. BILD/04/96. 41 S. 1. april 1996.
NVA Report
Solberg, Anne H. Schistad. (1996).
Tolkning av satellittbilder (i \Verdt å vite\")".
21. january 1996.
NVA Program participation
Solberg, Anne H. Schistad. (1996).
Texture fusion and classification based on flexible discriminant analysis.
Ukjent. 25. august 1996.
NVA Academic article
Solberg, Anne H. Schistad and Solberg, Rune. (1996).
A large-scale evaluation of features for automatic detection of oil spills in ERS SAR images.
Ukjent. 27. may 1996.
NVA Academic article
Solberg, Anne H. Schistad and Jain, Anil K.. (1995).
A Study of the invariance properties of textural features in SAR images.
Ukjent. 10. july 1995.
NVA Academic article
Solberg, Anne H. Schistad. (1995).
Data fusion and texture in classification of synthetic aperture radar imagery.
899. ISBN 9788253903972. 1. june 1995.
NVA Report
Solberg, Anne H S; Bosnes, Vidar; Storvik, Geir Olve and Bosnes, Vidar. (1995).
Tissue classification in MR images based on a mixed pixel model.
9th Scandinavian Conference on Image Analysis. 1. january 1995. Uppsala. Sweden.
NVA Scientific lecture
Milvang, Otto; Solberg, Anne H. Schistad; Andersen, Tove; Huseby, Ragnar Bang and Bjerde, Katrine Weisteen. (1995).
Seabed classification from sonar data. Report for 1992-94.
Norsk Regnesentral. BILD/03/95. 45 S. 1. january 1995.
NVA Report
Solberg, Anne H. Schistad. (1995).
Synthetic aperture sonar.
Norsk Regnesentral. BILD/01/95. 17 S. 1. january 1995.
NVA Report
Aas, Kjersti and Solberg, Anne H. Schistad. (1995).
Representative parameters from thin sections.
Norsk Regnesentral. BILD/07/95. 33 S. 1. january 1995.
NVA Report
Storvik, Geir Olve; Bølviken, Erik and Solberg, Anne H S. (1994).
Hidden Markov Chains for recognition of structures in time series.
Norsk Regnesentral. 880. -1 S.
NVA Report
Bjerde, Katrine Weisteen; Huseby, Ragnar Bang; Milvang, Otto and Solberg, Anne H. Schistad. (1994).
Xseabed user manual.
Norsk Regnesentral. BILD/02/94. 1. january 1994.
NVA Report
Milvang, Otto; Bjerde, Katrine Weisteen; Huseby, Ragnar Bang and Solberg, Anne H. Schistad. (1994).
Seabed classification from sonar data. Report for 1993.
Norsk Regnesentral. BILD/01/94. 25 S. 1. january 1994.
NVA Report
Solberg, Anne H. Schistad; Bosnes, Vidar and Storvik, Geir. (1994).
Tissue classification in MR images based on a mixed pixel model.
Ukjent. 13. june 1994.
NVA Academic article
Solberg, Anne H. Schistad; Jain, Anil K. and Taxt, Torfinn. (1994).
Multisource classification of remotely sensed data: fusion of Landsat TM and SAR images.
IEEE Transactions on Geoscience and Remote Sensing. ISSN 0196-2892 1558-0644. Vol. 32. Issue 4. S. 768-777. 1. january 1994.
NVA Academic article
Milvang, Otto; Andersen, Tove and Solberg, Anne H. Schistad. (1994).
Seabed classification from sonar data. Report of first half of 1994.
Norsk Regnesentral. BILD/07/94. 23 S. 1. january 1994.
NVA Report
Solberg, Anne H. Schistad and Taxt, Torfinn. (1994).
Classification of multisource satellite imagery based on a Markov random field model.
Ukjent. 26. september 1994.
NVA Academic article
Solberg, Anne H. Schistad. (1994).
A Markov random field model for classification of multisource satellite imagery.
Norsk Regnesentral. BILD/09/94. 27 S. 1. august 1994.
NVA Report
Koren, Hans; Solberg, Anne H. Schistad; Halck, Ole Martin and Solberg, Rune. (1994).
Texture analysis of sandstone surfaces.
Norsk Regnesentral. BILD/08/94. 36 S. 1. august 1994.
NVA Full text Report
Show summary
This report is the contribution from the Norwegian Computing Center (NR) to the workshop Flat Image Texture Analysis, August 29, 1994, organized by SINTEF. The objective of the workshop was to study possible textural features that can be applied to discriminate between different sandstone facies. Due to limited resources, only relevant textural operator currently available at NR were tested. These are GLCM features, Simultaneous Autoregressive (SAR) models, Gabor filters, at set of six miscellaneous local texture operators. The available data set consisted of four samples only, so we have been cautious in drawing any final conclusions. The experiments in the different spectral bands and (2) some of the textural features. Of the four sandstone facies parameters grain size, porosity, and contents of quartz and feldspar, we found indications of relationships between gray levels and the textural features. A relatively high correlation was found between gray gray level and the textural features GLCM Correlation, SAR textural features, Contrast and Homogeneity. Other textural features seem to have some discriminative properties, but at least they cannot be used separately. Before work on further adaption or development of textural operators is initiated, we strongly recommend that these textural features are tested statistically in a data set consisting on a few hundred samples.
Huseby, Ragnar Bang; Milvang, Otto; Solberg, Anne H. Schistad; Weisteen, Katrine; Madsen, Rune Asgeir; Kavli, Tom and Carlin, Mats. (1993).
Seafloor Classification. Report for 2. half of 1992.
Norsk Regnesentral. BILD/01/93. 43 S. 1. january 1993.
NVA Report
Huseby, Ragnar Bang; Milvang, Otto; Solberg, Anne H. Schistad and Weisteen, Katrine. (1993).
Seabed Classification from backscatter sonar data.
PIXEL'N. Issue 1. 1. january 1993.
NVA Popular scientific article
Milvang, Otto; Huseby, Ragnar Bang; Weisteen, Katrine and Solberg, Anne H. Schistad. (1993).
Feature extraction from backscatter sonar data.
Ukjent. 14. april 1993.
NVA Academic article
Huseby, Ragnar Bang; Milvang, Otto; Solberg, Anne H. Schistad and Weisteen, Katrine. (1993).
Seabed Classification from backscatter sonar data using statistical methods.
Ukjent. 14. april 1993.
NVA Academic article
Solberg, Anne H. Schistad; Jain, Anil K. and Taxt, Torfinn. (1993).
Fusion of multitemporal satellite images and GIS data for land-use classification.
Ukjent.
NVA Full text Academic article
Solberg, Anne H. Schistad and Taxt, Torfinn. (1993).
Datafusjon i klassifikasjon av satellittbilder.
Ukjent. S. 5-5. 19. february 1993.
NVA Academic article
Bosnes, Vidar; Solberg, Anne H S; Storvik, Geir Olve and Bosnes, Vidar. (1993).
Classification of mixed pixels.
870. -1 S.
NVA Report
Weisteen, Katrine; Solberg, Anne H. Schistad and Solberg, Rune. (1993).
Oil spill detection in SAR imagery - summary report.
Norsk Regnesentral. BILD/04A/93. 15 S. 1. february 1993.
NVA Report
Weisteen, Katrine; Solberg, Anne H. Schistad and Solberg, Rune. (1993).
Detection of oil spill in SAR images using a statistical classification scheme.
Ukjent. 18. august 1993.
NVA Academic article
Huseby, Ragnar Bang; Milvang, Otto; Solberg, Anne H. Schistad and Bjerde, Katrine Weisteen. (1993).
Seabed classification from multibeam echosunder data using statistical methods.
Ukjent. 18. october 1993.
NVA Academic article
Holbæk-Hanssen, Erik and Solberg, Anne H. Schistad. (1989).
Delvis styrt klassifikasjon av SAR-bilder over hav-is.
835. ISBN 9788253903279. 37 S. 1. january 1989.
NVA Report