Presented by M. Malini Deepika, Research Scholar, SASTRA University. Thanjavur. Tamilnadu. STEREO Earth Observers - Solar TErrestrial Relations Observatory - Two identical space cameras are launched - Single space craft carries two earth observing sensor Need for Stereo Earth Observers - Information of depth and width of the ravination Difficulty Behind Stereo Earth Observers - upholding the craft - Limitation in sensor - Life time of the Craft DLR- 3D Line Stereo scanner (1980) - offered to fly on SROSS-I (1988) - derive coarse Digital Surface Models (DSM) - 70 m ground resolution - German 3-line scanner MOMS-02 HRS Instrument on SPOT-5 - MOMS-02/D2 (1993) -MOMS-2P(1996-1999) - MOMS-03 - Special additions to S/w systems (stereo IKONOS-2 and QuickBird images ) Cartosat-I (2005) -E.Baltsaviaset.al., et.al. (2007) - Willneff. et.al., and Y.V.N. Murthy et.al (2008) - Giribabu (2014) Dual Camera Based Depth Camera Based Single Camera Based - Consecutive frame based methods - Depth estimation based method Hardware Complexity - Multiple camera - Multidimensional View Color distortions Retinal rivalry Ghosting Computational Intensity - Depth Estimation Based Methods Foreshortening Specular Surfaces Image Courtesy ISPRS To get anaglyph video sequence in real time Using Monocular Vision Real world projection of the object Estimating depth of the object Sensor Independent Data from any period can be used Step: 1 Acquire the scene Step: 2 Stereo pair is generated (m) The coordinates of Clone1 frame is defines as, A( x A, y A, z A ) ( x A b , y A , z A ) 2 (n) The coordinates of Clone2 frame is defines as, Ax A' , y A' , z A' x A' b , y A' , z A' 2 Step: 3 Colour component of the cloned frames A and A’ are changed as red and cyan Step: 4 The colour component converted cloned frame are superimposed to form the projection on the single frame. The projection is done by Euclidean geometry xA x x A' x A b 2 f ZA A' b z A' Step: 5 The anaglyph video is generated 2 f Agriculture Medical Defence Arts and Entertainment Virtual office Chi-Square test on Contrast in unprocessed PAN Image Distortion GN Motion SN Chi Value 0.295 0.4193 0.3987 p 0.001 0.009 0.007 Chi-Square test on Contrast in Anaglyph PAN Image Distortion GN Chi Value p 0.2677 0.008 GN-Gaussian Noise SN- Salt Noise Motion SN 0.422 0.3498 0.004 0.003 Chi-Square test on Contrast in source Multispectral Image Distortion GN Motion SN Chi value 0.3294 0.4219 0.3948 P 0.002 0.008 0.002 Chi-Square test on Contrast in Anaglyph MS Image Distortion GN Motion SN Chi value 0.2850 0.4439 0.3690 P 0.000 0.011 0.009 Advantages Easy Less Any implementation hardware complexity type of anaglyph image can be generated No image stabilization or rectification is required Giribabu D., Pramod Kumar, John Mathew, K.P. Sharma and Y.V.N. Krishna Murthy,2013. DEM generation using Cartosat-1 stereo data issues and complexities in Himalayan terrain in European Journal of Remote Sensing ,46,pp. 431-443. Hae-Yeoun Lee, Taejung Kim, Wonkyu Park, Heung Kyu Lee ,2003. Extraction of digital elevation models from satellite stereo images through stereo matching based on epipolarity and scene geometry in Image and Vision Computing, 21,pp. 789-796. Sreenivas Kandrika, R. S. Dwivedi,2013. Reclamative grouping of ravines using Cartosat-1 PAN Stereo Data in J Indian Soc Remote Sens , Sci Vis 41 (3),pp. 731-737.
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