Automatizing chromatic quality assessment for cultural heritage image digitization

Granados-Fontecha, Ana, Moreno-Pelayo, Valentín and Robledano-Arillo, Jesús Automatizing chromatic quality assessment for cultural heritage image digitization. El profesional de la información, 2019, vol. 28, n. 3. [Journal article (Unpaginated)]

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English abstract

In the context of digitization of photographs and other documents with graphical value, cultural heritage organizations need to give a guarantee that the stored digital image is a faithful representation of the physical image both at the physical level and the perceptual level. On the physical level, image quality can be measured objectively in a simple way by applying certain physical attributes to the image, as well as by measuring how distorting images affects the performance of the attributes. However, on the perceptual level, image quality should correspond to the perception that a human expert would experience when observing the physical image under certain determined and controlled conditions. In this paper we address the problem of image quality assessment (IQA) in the context of cultural heritage digitization by applying machine learning (ML). In particular, we explore the possibility of creating a decision tree that mimics the response of an expert on cultural heritage when observing cultural heritage images.

Item type: Journal article (Unpaginated)
Keywords: Photography collections; Cultural heritage digitization; Image quality assessment (IQA); Color; Machine learning (ML); Decision trees; Automatic classification; Learning model; Algorithms.
Subjects: I. Information treatment for information services > IH. Image systems.
J. Technical services in libraries, archives, museum. > JG. Digitization.
J. Technical services in libraries, archives, museum. > JH. Digital preservation.
Depositing user: Tomàs Baiget
Date deposited: 24 Sep 2019 17:07
Last modified: 24 Sep 2019 17:07
URI: http://hdl.handle.net/10760/39012

References

Aydin, Tunç-Ozan; Mantiuk, Rafal; Myszkowski, Karol; Seidel, Hans-Peter (2008). “Dynamic range independent image quality assessment”. ACM transactions on graphics, v. 27, n. 3, article n. 69.

http://resources.mpi-inf.mpg.de/hdr/vis_metric

Brandão, Tomás; Queluz, Maria-Paula (2008). “No-reference image quality assessment based on DCT domain statistics”. Signal processing, v. 88, n. 4, pp. 822-833.

https://doi.org/10.1016/j.sigpro.2007.09.017

Breiman, Leo (1996). “Bagging predictors”. Machine learning, v. 24, n. 2, pp. 123-140.

https://doi.org/10.1023/A:101805431

Cadík, Martin; Herzog, Robert; Mantiuk, Rafal; Myszkowski, Karol; Seidel, Hans-Peter (2012). “New measurements reveal weaknesses of image quality metrics in evaluating graphics artifacts”. ACM transactions on graphics, v. 31, n. 6, article n. 147.

https://doi.org/10.1145/2366145.2366166

Chang, Huiwen; Yu, Ficher; Wang, Jue; Ashley, Douglas; Finkelstein, Adam (2016). “Automatic triage for a photo series”. ACM transactions on graphics, v. 35, n. 4, article n. 148.

https://www.juew.org/publication/sig16-triage.pdf

https://doi.org/10.1145/2897824.2925908

Charrier, Christophe; Lézoray, Olivier; Lebrun, Gilles (2012). “Machine learning to design full-reference image quality assessment algorithm”. Signal processing: Image communication, v. 27, n. 3, pp. 209-219.

https://doi.org/10.1016/j.image.2012.01.002

De, Indrajit; Sil, Jaya (2011). “No reference image quality assessment using fuzzy relational classifier”. In: Deng Hepu; Miao, Duoquian; Lei, Jingsheng; Wang, Fu-Lee (eds.). Intl conf on artificial intelligence and computational intelligence. AICI 2011. Lecture notes in computer science, v. 7002, pp. 551-558. ISBN: 978 3 642 23880 2

https://doi.org/10.1007/978-3-642-23881-9_71

Engeldrum, Peter G. (1995). “A framework for image quality models”. Journal of imaging science and technology, v. 39, n. 4, pp. 312-318.

Engeldrum, Peter G. (2004). “A theory of image quality: The image quality circle”. Journal of imaging science and technology, v. 48, n. 5, pp. 446-456.

http://www.imcotek.com/pdf_temp/JIST_446-456_04_IQtheory.pdf

Fadgi (2010). Technical guidelines for digitizing cultural heritage materials: Creation of raster image master files. For the following originals - manuscripts, books, graphic illustrations, artwork, maps, plans, photographs, aerial photographs, and objects and artifacts. Federal Agencies Digitization Initiative; Still Image Working Group.

http://www.digitizationguidelines.gov/guidelines/FADGI_Still_Image-Tech_Guidelines_2010-08-24.pdf

Frey, Franzisca S.; Reilly, James M. (2006). Digital imaging for photographic collections: Foundations for technical standards (2nd ed.) Rochester, NY: Image Permanence Institute.

https://www.imagepermanenceinstitute.org/webfm_send/650

Gao, Xinbo; Gao, Fei; Tao, Dacheng; Li, Xuelog (2013). “Universal blind image quality assessment metrics via natural scene statistics and multiple kernel learning”. IEEE Transactions on neural networks and learning systems, v. 24, n. 12, pp. 2013-2026.

https://doi.org/10.1109/TNNLS.2013.2271356

Gastaldo, Paolo; Zunino, Rodolfo; Heynderickx, Ingrid; Vicario, Elena (2005). “Objective quality assessment of displayed images by using neural networks”. Signal processing: Image communication, v. 20, n. 7, pp. 643-661.

https://doi.org/10.1016/j.image.2005.03.013

Gastaldo, Paolo; Zunino, Rodolfo; Redi, Judith (2013). “Supporting visual quality assessment with machine learning”. Eurasip, Journal on image and video processing, n. 54, pp. 1-15.

Hall, Mark; Frank, Elbe; Holmes, Geoffrey; Pfahringer, Bernhard; Reutemann, Peter; Witten, Ian H. (2009). “The WEKA data mining software: An update”. Sigkdd Explorations, v. 11, n. 1, pp. 10-18.

https://doi.org/10.1186/1687-5281-2013-54

ISO (2008). ISO 11664-4:2008 (CIE S 014-4/E:2007). Colorimetry - Part 4: CIE 1976 L*a*b* colour space. Geneva, Switzerland: International Organization for Standardization.

ISO (2009). ISO 3664:2009. Graphic technology and photography - Viewing conditions. Geneva, Switzerland: International Organization for Standardization.

ISO (2012). ISO 20462-3:2012. Photography - Psychophysical experimental methods for estimating image quality - Part 3: Quality ruler method. Geneva, Switzerland: International Organization for Standardization.

ISO (2015). ISO 12646:2015. Graphic technology - Displays for colour proofing – Characteristics. Geneva, Switzerland: International Organization for Standardization.

ISO (2017a). ISO 19263-1:2017. Photography - Archiving systems. Part 1: Best practices for digital image capture of cultural heritage material. Geneva, Switzerland: International Organization for Standardization.

https://www.iso.org/obp/ui/#iso:std:iso:tr:19263:-1:ed-1:v1:en

ISO (2017b). ISO/TS 19264-1:2017. Photography - Archiving systems -- Image quality analysis - Part 1: Reflective originals. Geneva, Switzerland: International Organization for Standardization.

Kopf, Johannes; Kienzle, Wolf; Drucker, Steven; Kang, Sing-Bing (2012). “Quality prediction for image completion”. ACM transactions on graphics, v. 31, n. 6, article n. 131.

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.370.1764&rep=rep1&type=pdf

https://doi.org/10.1145/2366145.2366150

Kusuma, Tubagus-Maulana; Zepernick, Hans-Jürgen (2003). “A reduced-reference perceptual quality metric for in-service image quality assessment”. In: SympoTIC'03. Joint first Workshop on mobile future and Symposium on trends in communications. IEEE, pp. 71-74.

https://doi.org/10.1109/TIC.2003.1249092

Larson, Eric C.; Chandler, Damon M. (2010). “Most apparent distortion: Full-reference image quality assessment and the role of strategy”. Journal of electronic imaging, v. 19, n. 1, pp. 1-21.

https://s2.smu.edu/~eclarson/pubs/2010JEI_MAD.pdf

https://doi.org/10.1117/1.3267105

Li, Chaofeng; Bovik, Alan C.; Wu, Xiaojun (2011). “Blind image quality assessment using a general regression neural network”. IEEE Transactions on neural networks, v. 22, n. 5, pp. 793-799.

https://live.ece.utexas.edu/publications/2011/Li_tnn_2011.pdf

https://doi.org/10.1109/TNN.2011.2120620

Li, Qiang; Wang, Zhou (2009). “Reduced-reference image quality assessment using divisive normalization-based image representation”. IEEE Journal of selected topics in signal processing, v. 3, n. 2, pp. 202-211.

https://doi.org/10.1109/JSTSP.2009.2014497

Lin, Weisi; Kuo, C. C. Jay (2011). “Perceptual visual quality metrics: A survey”. Journal of visual communication and image representation, v. 22, n. 4, pp. 297-312.

https://doi.org/10.1016/j.jvcir.2011.01.005

Liu, Mohan; Konya, Iuliu; Nandzik, Jan; Flores-Herr, Nicolas; Eickeler, Stefan; Ndjiki-Nya, Patrick (2012). “A new quality assessment and improvement system for print media”. Eurasip, Journal on advances in signal processing, v. 2012, n. 109.

https://doi.org/10.1186/1687-6180-2012-109

Liu, Tsung-Jung; Lin, Weisi; Kuo, C. C. Jay (2013). “Image quality assessment using multi-method fusion”. IEEE transactions on image processing, v. 22, n. 5, pp. 1793-1807.

https://www.researchgate.net/publication/234047751_Image_Quality_Assessment_Using_Multi-Method_Fusion

https://doi.org/10.1109/TIP.2012.2236343

Luo, Ming-Ronnier; Cui, Guihua; Rigg, Bryan (2001). “The development of the CIE 2000 colour-difference formula: CIEDE2000”. Color research & application, v. 26, n. 5, pp. 340-350.

https://www.researchgate.net/publication/229511830_The_development_of_the_CIE_2000_colour-difference_formula_CIEDE2000

https://doi.org/10.1002/col.1049

Ma, Lin; Li, Songnan; Zhang, Fan; Ngan, King-Ngi (2011). “Reduced-reference image quality assessment using reorganized DCT-based image representation”. IEEE Transactions on multimedia, v. 13, n. 4, pp. 824-829.

https://doi.org/10.1109/TMM.2011.2109701

Major, John A.; Mangano, John J. (1995). “Selecting among rules induced from a hurricane database”. Journal of intelligent information systems, v. 4, n. 1, pp. 39-52.

https://doi.org/10.1007/BF00962821

Mantiuk, Rafat; Kim, Kil-Joong; Rempel, Allan G.; Heidrich, Wolfgang (2011). “HDR-VDP-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions”. ACM Transactions on graphics, v. 30, n. 4, article n. 40.

http://hdrvdp.sourceforge.net/hdrvdp.pdf

https://doi.org/10.1145/2010324.1964935

Mittal, Anish; Moorthy, Anush-Krishna; Bovik, Alan C. (2012). “No-reference image quality assessment in the spatial domain”. IEEE Transactions on image processing, v. 21, n. 12, pp. 4695-4708.

https://doi.org/10.1109/TIP.2012.2214050

Narwaria, Manish; Lin, Weisi; Cetin, A. Enis (2012). “Scalable image quality assessment with 2D mel-cepstrum and machine learning approach”. Pattern recognition, v. 45, n. 1, pp. 299-313.

https://doi.org/10.1016/j.patcog.2011.06.023

Nationaal Archief of the Netherlands (2010). Digitisation of photographic materials. Guidelines. September 2010.

https://www.nationaalarchief.nl/sites/default/files/field-file/guidelines_digitisation_photographic_materials.pdf

Oeztireli, A. Cengiz; Gross, Markus (2015). “Perceptually based downscaling of images”. ACM Transactions on graphics, v. 34, n. 4, article n. 77.

https://people.inf.ethz.ch/~cengizo/Files/Sig15PerceptualDownscaling.pdf

https://doi.org/10.1145/2766891

Ponomarenko, Nikolay; Jin, Lina; Ieremeiev, Oleg; Lukin, Vladimir; Egiazarian, Karen; Astola, Jaakko; Vozel, Benoit; Chehdi, Kacem; Carli, Marco; Battisti, Federica; Kuo, C. C. Jay (2015). “Image database TID2013: Peculiarities, results and perspectives”. Signal processing: Image communication, v. 30, pp. 57-77.

https://doi.org/10.1016/j.image.2014.10.009

Puglia, Steven; Reed, Jeffrey; Rhodes, Erin (2004). Technical guidelines for digitizing archival materials for electronic access: Creation of production master files - Raster images. U. S. National Archives and Records Administration (NARA).

https://www.archives.gov/files/preservation/technical/guidelines.pdf

Quinlan, J. Ross (1992). C4.5: Programs for machine learning. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc. ISBN: 978 1 558602380

Robledano-Arillo, Jesús; Navarro-Bonilla, Diego (2017). “Aproximación sistemática a la creación de versiones digitales de negativos fotográficos históricos”. El profesional de la información, v. 26, n. 6, pp. 1172-1183.

https://doi.org/10.3145/epi.2017.nov.16

Robledano-Arillo, Jesús (2016). “25 years of digital conversión, state of the art”. In: Conservation of photographs: 30 years of science. Pamplona, Spain: CAAP. ISBN: 978 84 608 4647 5

Robledano-Arillo, Jesús; Moreno-Pelayo, Valentín; Pereira-Uzal, José-Manuel (2016). “Aproximación experimental al uso de métricas objetivas para la estimación de calidad cromática en la digitalización de patrimonio documental gráfico”. Revista española de documentación científica, v. 39, n. 2.

https://doi.org/10.3989/redc.2016.2.1249

English version on:

https://e-archivo.uc3m.es/handle/10016/23693

Sheikh, Hamid R.; Sabir, Muhammad-Farooq; Bovik, Alan C. (2006). “A statistical evaluation of recent full reference image quality assessment algorithms”. IEEE Transactions on image processing, v. 15, n. 11, pp. 3440-3451.

http://03c91d6.netsolhost.com/PDF/Statistic-of-Full-Reference-UT.pdf

https://doi.org/10.1109/TIP.2006.881959

Sheikh, Hamid R.; Bovik, Alan C. (2006). “Image information and visual quality”. IEEE Transactions on image processing, v. 15, n. 2, pp. 430-444.

https://live.ece.utexas.edu/publications/2004/hrs_ieeetip_2004_imginfo.pdf

https://doi.org/10.1109/TIP.2005.859378

Sheikh, Hamid R.; Bovik, Alan C.; Cormack, Lawrence (2005). “No-reference quality assessment using natural scene statistics: JPEG2000”. IEEE Transactions on image processing, v. 14, n. 11, pp. 1918-1927.

https://www.researchgate.net/publication/3328029_No-reference_quality_assessment_using_natural_scene_statistics_JPEG2000

https://doi.org/10.1109/TIP.2005.854492

Suresh, Sundaram; Babu, R. Venkatesh; Kim, Hyoung J. (2009). “No-reference image quality assessment using modified extreme learning machine classifier”. Applied soft computing, v. 9, n. 2, pp. 541-552.

https://doi.org/10.1016/j.asoc.2008.07.005

Van-Dormolen, Hans (2012). Metamorfoze preservation imaging guidelines. Image quality, version 1.0. National Archives of the Neetherlands. January 2012.

https://www.metamorfoze.nl/sites/metamorfoze.nl/files/publicatie_documenten/Metamorfoze_Preservation_Imaging_Guidelines_1.0.pdf

Wang, Zhou; Bovik, Alan C.; Sheikh, Hamid R.; Simoncelli, Eero-Peter (2004). “Image quality assessment: From error visibility to structural similarity”. IEEE Transactions on image processing, v. 13, n. 4, pp. 600-612.

http://www.cns.nyu.edu/pub/lcv/wang03-preprint.pdf

https://doi.org/10.1109/TIP.2003.819861

Wang, Zhou; Simoncelli, Eero P. (2005). “Reduced-reference image quality assessment using a wavelet-domain natural image statistic model”. In: Rogowitz, Bernice E.; Pappas, Thrasyvoulos N.; Daly, Scott J. (eds.). Proceedings of SPIE. Human vision and electronic imaging X (18 March 2995), v. 5666, pp. 149-159.

https://doi.org/10.1117/12.597306

Wang, Zhou; Simoncelli, Eero P.; Bovik, Alan C. (2003). “Multi-scale structural similarity for image quality assessment”. In: Matthews, M. B. (ed.). The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, v. 2, pp. 1398-1402.

https://doi.org/10.1109/ACSSC.2003.1292216

Williams, Don; Longman, Jere (2003). “Debunking specsmanship: Progress on ISO/TC42 standards for digital capture imaging performance”. In: IS&T PICS Conference, pp. 77-81.

Zhao, Yang; Campisi, Patrizio; Kundur, Deepa (2004). “Dual domain watermarking for authentication and compression of cultural heritage image”. IEEE Transactions on image processing, v. 13, n. 3, pp. 430-448.

https://doi.org/10.1109/TIP.2003.821552

Zhang, Lin; Zhang, Lei; Mou, Xuanqin; Zhang, David (2011). “FSIM: A feature similarity index for image quality assessment”. IEEE Transactions on image processing, v. 20, n. 8, pp. 2378-2386.

https://www4.comp.polyu.edu.hk/~cslzhang/IQA/TIP_IQA_FSIM.pdf

https://doi.org/10.1109/TIP.2011.2109730


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