Zastosowanie nowoczesnych metod oceny jakości obrazów do weryfikacji algorytmów splattingu w subpikselowej metodzie Image Based Rendering

• Autorzy: Okarma K. , Tecław M.

Warianty tytułu

EN

Application of modern image quality assessment methods to verification of splatting algorithms in the sub-pixel Image Based Rendering

• Języki publikacji: PL

Abstrakty

PL

W artykule przedstawiono możliwości wykorzystania nowoczesnych wskaźników jakości obrazów do wyboru i weryfikacji algorytmu splattingu służącego do wypełniania brakujących pikseli w metodzie IBR, a także do wyboru obrazu wyjściowego dla algorytmu splattingu. Dzięki zastosowaniu metod automatycznej oceny jakości obrazów możliwy jest wybór właściwego algorytmu splattingu wykorzystującego współrzędne uzyskiwanych punktów z dokładnością subpikselową, co zapewnia dużo wyższą jakość obrazu wynikowego.

EN

The paper presents possibilities of using some modern image quality assessment methods for choice and verification of the splatting algorithm used to fill some missing pixels in the IBR method, as well as for selection of the basic output image for the splatting algorithm. By using automatic image quality assessment methods, it is possible to choose the accurate splatting algorithm which utilizes the coordinates of points with sub-pixel accuracy and provides much higher quality of the output image. The first discussed approach is the idea of Vector Median Splatting based on the vector median filters used mainly for multichannel nonlinear filtering purposes. Since the main goal of splatting is filling the missing pixels by the most similar colour to its nearest neighbourhood, preventing the sharpness of the obtained image, such algorithm allows achieving satisfactory results. Nevertheless, even better results can be achieved by some sub-pixel based methods preventing the loss of information caused by the rounding of the pixels coordinates after the warping operation. The results of the application of some modified algorithms have been verified using some modern image quality assessment methods, mainly based on the similarity of images, such as e.g. Structural Similarity or recently proposed Feature Similarity index. The advantages of the sub-pixel splatting algorithms have been confirmed by higher values of all image quality metrics calculated for the achieved destination images.

Słowa kluczowe

PL

metoda IBR; splatting; ocena jakości obrazów

EN

IBR; splatting; image quality assessment

• Wydawca: Wydawnictwo PAK
• Czasopismo: Pomiary Automatyka Kontrola
• Rocznik: 2012
• Tom: R. 58, nr 6
• Strony: 493--497
• Opis fizyczny: Bibliogr. 11 poz., rys., tab., wzory

Twórcy

autor

Okarma K.

autor

Tecław M.

• Zachodniopomorski Uniwersytet Technologiczny w Szczecinie, Katedra Przetwarzania Sygnałów i Inżynierii Multimedialnej, ul. 26 kwietnia 10, 71-126 Szczecin,

Bibliografia

• [1] McMillan L.: An Image Based Approach to Three-Dimensional Computer Graphics. PhD thesis, University of North Carolina, Chapel Hill, USA, 1997.
• [2] Okarma K., Miętus A., Tecław M.: Vector Median Splatting for Image Based Rendering. Lecture Notes in Computer Science vol. 6375, pp. 150-157, 2010.
• [3] Artist-3D.com, http://www.artist-3d.com
• [4] 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, pp. 600-612, 2004.
• [5] Wang Z., Simoncelli E., Bovik A.: Multi-Scale Structural Similarity for Image Quality Assessment. Proceedings of the 37th IEEE Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, USA, 2003.
• [6] Zhang L., Zhang L., Mou X., Zhang D.: FSIM: A Feature Similarity Index for Image Quality Assessment. IEEE Transactions on Image Processing vol. 20, no. 8, pp. 2378-2386, 2011.
• [7] Wang Z., Bovik A.: A Universal Image Quality Index. IEEE Signal Processing Letters vol. 9, no. 3, pp. 81-84, 2002.
• [8] Okarma K., Miętus A.: Application of Image Based Rendering for the improvement of face recognition using Principal Component Analysis. Pomiary Automatyka Kontrola vol. 56, no. 12, pp.1495-1497, 2010.
• [9] Komorowski J., Rokita P.: Pose Invariant Face Recognition Method Using Stereo Vision. Advanced in Intelligent and Soft Computing, vol. 95, pp. 13-22, 2011.
• [10] Okarma K.: Combined Full-Reference Image Quality Metric Linearly Correlated with Subjective Assessment. Lecture Notes in Artificial Intelligence vol. 6113, pp. 539-546, 2010.
• [11] Okarma K.: Influence of the 2D sliding windows on the correlation of the digital image quality assessment results using the Structural Similarity approach with the subjective evaluation. Przegląd Elektrotechniczny vol. 86, no. 7, pp. 109-111, 2010.