Colour interpolation for sub-pixel Image Based Rendering

• Autorzy: Okarma K. , Tecław M.
• Konferencja: Computer Applications in Electrical Engineering 2012 (23-24.04.2012; Poznań, Polska)
• Języki publikacji: EN

Abstrakty

EN

Image Based Rendering (IBR) is one of the most efficient approaches to the real-time computer visualisation. Applying the warping equation, being the essence of this method, it is possible to render the image observed by a virtual camera assuming the knowledge of the image and the depth map taken by another camera or cameras located at different positions. Nevertheless, depending on the geometrical configuration of the reference and destination (virtual) cameras some holes in the destination image can be observed. Their presence is caused by the fact that some fragments of objects visible from the destination camera may be not present in the reference images. A typical approach to filling such holes is splatting but typical algorithms usually cause the loss of details. Nevertheless, using the sub-pixel IBR based on the combination of the images taken from two or more cameras, the problem of missing data can be partially solved due to the possibility of the 2D or 3D interpolation, considering also the depth values of the projected points in the second case. The results obtained using the proposed approach have been verified using some recently proposed full-reference image quality assessment methods using the synthetic image of the 3D object as the reference image.

Słowa kluczowe

EN

image-based rendering; IBR; computer visualisation

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Poznan University of Technology Academic Journals. Electrical Engineering
• Rocznik: 2012
• Tom: No. 71
• Strony: 193--199
• Opis fizyczny: Bibliogr. 6 poz., rys.

Twórcy

autor

Okarma K.

• West Pomeranian University of Technology, Szczecin

autor

Tecław M.

• West Pomeranian University of Technology, Szczecin

Bibliografia

• [1] McMillan L., An Image-Based Approach to Three-Dimensional Computer Graphics, Ph.D. Thesis, University of North Carolina, Chapel Hill, 1997.
• [2] Okarma, K., Miętus, A., Tecław, M., Vector Median Splatting for Image Based Rendering, Lecture Notes in Computer Science, Volume 6375, pp. 150-157, 2010.
• [3] 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, 2003.
• [4] Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E., Image Quality Assessment: From Error Measurement to Structural Similarity. IEEE Transactions on Image Processing, Volume 13, Number 4, pp. 600-612, 2004.
• [5] Zhang, L., Zhang, L., Mou, X. , Zhang, D., FSIM: A Feature Similarity Index for Image Quality Assessment, IEEE Transactions on Image Processing, Volume 20, Number 8, pp. 2378-2386, 2011.
• [6] 3D Artists Gallery http://artist-3d.com/free_3d_models.