Depth extraction in computational integral imaging based on bilinear interpolation

• Autorzy: Huang Huihua , Ge Peng

Identyfikatory

DOI

10.37190/oa200401

• Języki publikacji: EN

Abstrakty

EN

We proposed a method using a merit function to determine the depth of objects in computational integral imaging by analyzing the existing methods for depth extraction of target objects. To improve the resolution of reconstructed slice images, we use a digital camera moving in horizontal and vertical direction with the set interval to get elemental images with high resolution and bilinear interpolation algorithm to increase the number of pixels in slice image which improves the resolution obviously. To show the feasibility of the proposed method, we carried out our experiment and presented the results. We also compared it with other merit functions. The results show that merit function SMD2 to determine the depth of objects is more accurate and suitable for real-time application.

Słowa kluczowe

EN

computational integral imaging; depth extraction; bilinear interpolation algorithm

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Optica Applicata
• Rocznik: 2020
• Tom: Vol. 50, nr 4
• Strony: 497--509
• Opis fizyczny: Bibliogr. 16 poz., rys., tab.

Twórcy

autor

Huang Huihua

• School of Physics and Opto-electronic, South China University of Technology, Guangzhou, 510640, China

autor

Ge Peng

• School of Physics and Opto-electronic, South China University of Technology, Guangzhou, 510640, China

Bibliografia

• [1] WANG T.C., EFROS A.A., RAMAMOORTHI R., Occlusion-aware depth estimation using light-field cameras, 2015 IEEE International Conference on Computer Vision (ICCV), December 7–13, 2015, Santiago, Chile, pp. 3487–3495, DOI:10.1109/ICCV.2015.398.
• [2] WANG C., SAHIN E., SUOMINEN O., GOTCHEV A., Depth estimation by combining stereo matching and coded aperture, 2014 IEEE Visual Communications and Image Processing Conference, December 7–10, 2014, Valletta, Malta, pp. 291–294, DOI:10.1109/VCIP.2014.7051561.
• [3] WANG T.C., EFROS A.A., RAMAMOORTHI R., Depth estimation with occlusion modeling using light-field cameras, IEEE Transactions on Pattern Analysis and Machine Intelligence 38(11), 2016, pp. 2170–2181, DOI:10.1109/TPAMI.2016.2515615.
• [4] JANG J.Y., SER J.I., CHA S., SHIN S.H., Depth extraction by using the correlation of the periodic function with an elemental image in integral imaging, Applied Optics 51(16), 2012, pp. 3279–3286, DOI:10.1364/AO.51.003279.
• [5] SAID Z., SUNDARAJ K., WAHAB M.N.A., Depth estimation for a mobile platform using monocular vision, Procedia Engineering 41, 2012, pp. 945–950, DOI:10.1016/j.proeng.2012.07.267.
• [6] LONG H.M., GUO H.Y., LIANG F., LIU G.H., Distance measurement algorithm based on binocular stereo vision, Applied Mechanics and Materials 635–637, 2014, pp. 948–952, DOI:10.4028/www.scientific.net/AMM.635-637.948.
• [7] LIU W., WANG Z., NING X., ZHANG X., An object recognition and location based on binocular stereo vision, 2009 International Forum on Computer Science-Technology and Applications, December 25–27, 2009, Chongqing, China, pp. 490–492, DOI:10.1109/IFCSTA.2009.262.
• [8] LIPPMANN G., Épreuves réversibles donnant la sensation du relief, Journal de Physique Théoriqueet Appliquée 7(1), 1908, pp. 821–825, DOI:10.1051/jphystap:019080070082100.
• [9] LEE J.J., LEE B.G., YOO H., Depth extraction of three-dimensional objects using block matching for slice images in synthetic aperture integral imaging, Applied Optics 50(29), 2011, pp. 5624–5629, DOI:10.1364/AO.50.005624.
• [10] YOO H., Depth extraction for 3D objects via windowing technique in computational integral imaging with a lenslet array, Optics and Lasers in Engineering 51(7), 2013, pp. 912–915, DOI:10.1016/j.optlaseng.2013.02.009.
• [11] ZHAO X., WANG Y., SONG L., ZHANG B., ZHAO X., Underwater target imaging based on computational integral imaging, Chinese Journal of Lasers 45(1), 2018, article 0109001 (in Chinese), DOI:10.3788/CJL201845.0109001.
• [12] LI Y., CHEN N., ZHANG J., Fast and high sensitivity focusing evaluation function, Application Research of Computers 27(4), 2010, pp. 1534–1536 (in Chinese).
• [13] XIAO X., JAVIDI B., MARTINEZ-CORRAL M., STERN A., Advances in three-dimensional integral imaging: sensing, display, and applications [Invited], Applied Optics 52(4), 2013, pp. 546–560, DOI:10.1364/AO.52.000546.
• [14] HONG S.H., JANG J.S., JAVIDI B., Three-dimensional volumetric object reconstruction using computational integral imaging, Optics Express 12(3), 2004, pp. 483–491, DOI:10.1364/OPEX.12.000483.
• [15] SHIN D.H., YOO H., Computational integral imaging reconstruction method of 3D images using pixel-to-pixel mapping and image interpolation, Optics Communications 282(14), 2009, pp. 2760–2767, DOI:10.1016/j.optcom.2009.04.008.
• [16] DO C.M., JAVIDI B., 3D integral imaging reconstruction of occluded objects using independent component analysis-based k-means clustering, Journal of Display Technology 6(7), 2010, pp. 257–262.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).