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Tytuł artykułu

Accelerated image quality estimation based on the Monte Carlo approach for various types of image distortions

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Warianty tytułu
Konferencja
Computer Applications in Electrical Engineering 2010 [Poznań, April 19-21, 2010]
Języki publikacji
EN
Abstrakty
EN
In the paper the application of the Monte Carlo method for the fast estimation of image quality is investigated. Taking into account the variety of possible distortions present in the images, probably the largest publicly available database of 1700 images with 17 types of distortions has been used for the practical verification of the proposed approach. The analysis has been performed for some of the "state-of-the-art" image quality metrics as an alternative to the classical ones together with the comparison to well known Peak Signal to Noise Ratio.
Rocznik
Tom
Strony
157--165
Opis fizyczny
Bibliogr. 17 poz.
Twórcy
autor
  • West Pomeranian University of Technology, Szczecin
Bibliografia
  • [1] Shnayderman A., Gusev A., Eskicioglu A.: An SVD-Based Gray-Scale Image Quality Measure for Local and Global Assessment. IEEE Transactions on Image Processing, vol. 15 no. 2 (2006), pp. 422-429.
  • [2] Eskicioglu A., Fisher P., Chen S.: Image Quality Measures and Their Performance. IEEE Transactions on Communications, vol. 43 no. 12 (1995), pp. 2959-2965.
  • [3] Wang Z., Bovik A., Sheikh H., Simoncelli E.: Image Quality Assessment: From Error Measurement to Structural Similarity. IEEE Transactions on Image Processing vol. 13 no. 4 (2004), pp. 600-612.
  • [4] Wang Z., Simoncelli E., Bovik A.: Multi-Scale Structural Similarity for Image Quality Assessment. In: Proc. 37th IEEE Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA (2003).
  • [5] Sheikh H., Wang Z., Cormack L., Bovik A.: LIVE Image Quality Assessment Database Release 2. http://live.ece.utexas.edu/research/quality.
  • [6] Ponomarenko N., Carli M., Lukin V., Egiazarian K., Astola J., Battisti F.: Color Image Database for Evaluation of Image Quality Metrics. Proceedings of International Workshop on Multimedia Signal Processing, Australia, October 2008, pp. 403-408.
  • [7] Seshadrinathan K.., Soundararajan R., Bovik A., Cormack L.: Study of Subjective and Objective Quality Assessment of Video, IEEE Transactions on Image Processing vol. 19 no. 6 (2010), pp. 1427-1441.
  • [8] Seshadrinathan K., Soundararajan R., Bovik A., Cormack L.: A Subjective Study to Evaluate Video Quality Assessment Algorithms. SPIE Proceedings Human Vision and Electronic Imaging vol. 7527, 2010.
  • [9] Moorthy A.K., Seshadrinathan K., Soundararajan R., Bovik A.: Wireless video quality assessment: A study of subjective scores and objective algorithms. IEEE Transactions on Circuits and Systems for Video Technology vol. 20 no. 4 (2010), pp. 513-516.
  • [10] Moorthy A.K., Seshadrinathan K., Soundararajan R., Bovik A.: LIVE Wireless Video Quality Assessment Database (2009). http://live.ece.utexas.edu/research/quality/live_wireless_video.html
  • [11] Mazurek P., Okarma K..: An efficient estimation of the Structural Similarity index using the GPGPU programming techniques. Pomiary Automatyka Kontrola, vol. 56 no. 7 (2010), pp. 668-670.
  • [12] Chen M.-J., Bovik A.: Fast structural similarity index algorithm. Journal of Realtime Image Processing, Springer Verlag 2010, DOI 10.1007/s 11554-010-0170-9
  • [13] Mahmoudi-Aznaveh A., Mansouri A., Torkamani-Azar F., Eslami M. Image quality measurement besides distortion type classifying. Optical Review vol. 16 no. 1 (2009) pp. 30-34.
  • [14] Mansouri A., Mahmoudi-Aznaveh A., Torkamani-Azar F., Jahanshahi J.A.: Image quality assessment using the Singular Value Decomposition theorem. Optical Review vol. 16 no. 2 (2009) pp. 49-53.
  • [15] Okarma K..: Colour image quality assessment using Structural Similarity index and Singular Value Decomposition. Lecture Notes in Computer Science vol. 5337, Springer-Verlag (2009) pp. 55-65.
  • [16] Okarma K.: Combined full-reference image quality metric linearly correlated with subjective assessment. Lecture Notes in Artificial Intelligence vol. 6113, Springer-Verlag (2010) pp. 539-546.
  • [17] Okarma K.., Lech P.: A statistical reduced-reference approach to digital image quality assessment. Lecture Notes in Computer Science vol. 5337, Springer-Verlag (2009) pp. 43-54.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPP4-0002-0059
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