Research Article
Year 2017,
Volume: 2 Issue: 1, 35 - 40, 01.02.2017
Abstract
References
- Ahmed N., Natarajan T., and Rao K., 1974. Discrete cosine transform, IEEE Trans. Comput., vol. C-23, pp.90 -93 1974.
- Akcay, O., 2015. Landslide Fissure Inference Assessment by ANFIS and Logistic Regression Using UAS-Based Photogrammetry. ISPRS International Journal of Geo-Information, 4(4), 2131-2158.
- Avsar, E. Ö., Altan, M. O., Doğan, Ü. A., and Akça, D., 2015. Determining Pull-Out Deformations by Means of an Online Photogrammetry Monitoring System. International Journal of Environment and Geoinformatics, 2(1).
- Bay, H., Tuytelaars, T., and Van Gool, L., 2006. Surf: Speeded up robust features. In Computer vision–ECCV 2006 pp. 404-417. Springer Berlin Heidelberg.
- Chao, J., Chen, H., and Steinbach, E., 2013. On the design of a novel JPEG quantization table for improved feature detection performance. In Image Processing (ICIP), 2013 20th IEEE International Conference on (pp. 1675-1679). IEEE.
- Christopoulos, C.A. , Skodras, A.N. and Ebrahimi, T., 2000. The JPEG 2000 still image coding system: An overview, IEEE Trans. Consumer Electron, vol. 46, pp.1103 -1127 2000.
- Cronk S., 2001. The Effects of JPEG Image Compression On Digital Close-Range Photogrammetry, Report, Melbourne.
- Furukawa Y. and Ponce J., 2007 Accurate, Dense, and Robust Multi-View Stereopsis, CVPR 2007.
- Hamilton. E., 1992. JPEG File Interchange Format - Version 1.02. C-Cube Microsystems, Sep 1992.
- Huffman, D. A., 1952. A method for the construction of minimum redundancy codes, Proc. IRE, vol. 40, pp.1098 -1101 1952.
- Kerr D. A., 2012. Chrominance Subsampling in Digital Images. http://dougkerr.net/pumpkin/articles/Subsampling.pdf, Jan. 2012.
- Kyle, S., 2013. Close-Range Photogrammetry and 3D Imaging; Walter de Gruyter: Berlin, Germany; ISBNISSN: 9783110302783.
- Liang Z. , Xinming T. and Lin L., 2006. Effects of JPEG 2000 compression on remote sensing image quality, In Proc. of IEEE International Geoscience and Remote Sensing Symposium, pp. 3297-3300, July 2006.
- Luhmann, T., Fraser, C., and Maas, H. G., 2015. Sensor modelling and camera calibration for close-range photogrammetry. ISPRS Journal of Photogrammetry and Remote Sensing.
- Lowe, D. G., 2004. Distinctive image features from scale-invariant keypoints., International Journal of Computer Vision, 60, 2, pp. 91-110.
- Nouwakpo, S. K., Weltz, M. A., and McGwire, K., 2015. Assessing the performance of structure‐from‐ motion photogrammetry and terrestrial LiDAR for reconstructing soil surface microtopography of naturally vegetated plots. Earth Surface Processes and Landforms. 41(3) 308-322.
- Remondino, F., Spera, M.G., Nocerino, E., Menna, F. and Nex, F., 2014. State of the art in high density image matching. Photogramm. Rec., 29, 144–166.
- Seitz, S. M., Curless, B., Diebel, J., Scharstein, D., and Szeliski, R., 2006. A comparison and evaluation of multi-view stereo reconstruction algorithms. In Computer vision and pattern recognition, 2006 IEEE Computer Society Conference on, 1, 519-528. IEEE.
- Xiao, K., Zardawi, F., van Noort, R., and Yates, J. M., 2014. Developing a 3D colour image reproduction system for additive manufacturing of facial prostheses. The International Journal of Advanced Manufacturing Technology, 70(9-12), 2043-2049.
- Yilmaz, H. M., Yakar, M., Gulec, S. A., and Dulgerler, O. N., 2007. Importance of digital close-range photogrammetry in documentation of cultural heritage. Journal of Cultural Heritage, 8(4), 428-433.
- Yılmaztürk, F., 2011. Full-automatic self-calibration of color digital cameras using color targets. Optics express, 19(19), 18164-18174.
- Yılmaztürk F., Akçay Ö., 2005. Jpeg Görüntü Sıkıştırmanın Yakın Mesafe Dijital Fotogrametri Üzerindeki Etkileri, s. 918-925, 10. Türkiye Harita Bilimsel ve Teknik Kurultayı, Ankara, Türkiye, 28.03.2005 - 01.04.2005.
Year 2017,
Volume: 2 Issue: 1, 35 - 40, 01.02.2017
Abstract
Digital photogrammetry, using digital camera images, is an important low-cost engineering method to produce precise three-dimensional model of either an object or the part of the earth depending on the image quality. Photogrammetry which is cheaper and more practical than the new technologies such as LIDAR, has increased point cloud generation capacity during the past decade with contributions of computer vision. Images of new camera technologies needs huge storage space due to larger image file sizes. Moreover, this enormousness increases image process time during extraction, orientation and dense matching. The Joint Photographic Experts Group (JPEG) is one of the most commonly used methods as lossy compression standard for the storage purposes of the oversized image file. Particularly, image compression at different rates causes image deteriorations during the processing period. Therefore, the compression rates affect accuracy of photogrammetric measurements. In this study, the close range images compressed at the different levels were investigated to define the compression effect on photogrammetric results, such as orientation parameters and 3D point cloud. The outcomes of this study show that lower compression ratios are acceptable in photogrammetric process when moderate accuracy is sufficient.
References
- Ahmed N., Natarajan T., and Rao K., 1974. Discrete cosine transform, IEEE Trans. Comput., vol. C-23, pp.90 -93 1974.
- Akcay, O., 2015. Landslide Fissure Inference Assessment by ANFIS and Logistic Regression Using UAS-Based Photogrammetry. ISPRS International Journal of Geo-Information, 4(4), 2131-2158.
- Avsar, E. Ö., Altan, M. O., Doğan, Ü. A., and Akça, D., 2015. Determining Pull-Out Deformations by Means of an Online Photogrammetry Monitoring System. International Journal of Environment and Geoinformatics, 2(1).
- Bay, H., Tuytelaars, T., and Van Gool, L., 2006. Surf: Speeded up robust features. In Computer vision–ECCV 2006 pp. 404-417. Springer Berlin Heidelberg.
- Chao, J., Chen, H., and Steinbach, E., 2013. On the design of a novel JPEG quantization table for improved feature detection performance. In Image Processing (ICIP), 2013 20th IEEE International Conference on (pp. 1675-1679). IEEE.
- Christopoulos, C.A. , Skodras, A.N. and Ebrahimi, T., 2000. The JPEG 2000 still image coding system: An overview, IEEE Trans. Consumer Electron, vol. 46, pp.1103 -1127 2000.
- Cronk S., 2001. The Effects of JPEG Image Compression On Digital Close-Range Photogrammetry, Report, Melbourne.
- Furukawa Y. and Ponce J., 2007 Accurate, Dense, and Robust Multi-View Stereopsis, CVPR 2007.
- Hamilton. E., 1992. JPEG File Interchange Format - Version 1.02. C-Cube Microsystems, Sep 1992.
- Huffman, D. A., 1952. A method for the construction of minimum redundancy codes, Proc. IRE, vol. 40, pp.1098 -1101 1952.
- Kerr D. A., 2012. Chrominance Subsampling in Digital Images. http://dougkerr.net/pumpkin/articles/Subsampling.pdf, Jan. 2012.
- Kyle, S., 2013. Close-Range Photogrammetry and 3D Imaging; Walter de Gruyter: Berlin, Germany; ISBNISSN: 9783110302783.
- Liang Z. , Xinming T. and Lin L., 2006. Effects of JPEG 2000 compression on remote sensing image quality, In Proc. of IEEE International Geoscience and Remote Sensing Symposium, pp. 3297-3300, July 2006.
- Luhmann, T., Fraser, C., and Maas, H. G., 2015. Sensor modelling and camera calibration for close-range photogrammetry. ISPRS Journal of Photogrammetry and Remote Sensing.
- Lowe, D. G., 2004. Distinctive image features from scale-invariant keypoints., International Journal of Computer Vision, 60, 2, pp. 91-110.
- Nouwakpo, S. K., Weltz, M. A., and McGwire, K., 2015. Assessing the performance of structure‐from‐ motion photogrammetry and terrestrial LiDAR for reconstructing soil surface microtopography of naturally vegetated plots. Earth Surface Processes and Landforms. 41(3) 308-322.
- Remondino, F., Spera, M.G., Nocerino, E., Menna, F. and Nex, F., 2014. State of the art in high density image matching. Photogramm. Rec., 29, 144–166.
- Seitz, S. M., Curless, B., Diebel, J., Scharstein, D., and Szeliski, R., 2006. A comparison and evaluation of multi-view stereo reconstruction algorithms. In Computer vision and pattern recognition, 2006 IEEE Computer Society Conference on, 1, 519-528. IEEE.
- Xiao, K., Zardawi, F., van Noort, R., and Yates, J. M., 2014. Developing a 3D colour image reproduction system for additive manufacturing of facial prostheses. The International Journal of Advanced Manufacturing Technology, 70(9-12), 2043-2049.
- Yilmaz, H. M., Yakar, M., Gulec, S. A., and Dulgerler, O. N., 2007. Importance of digital close-range photogrammetry in documentation of cultural heritage. Journal of Cultural Heritage, 8(4), 428-433.
- Yılmaztürk, F., 2011. Full-automatic self-calibration of color digital cameras using color targets. Optics express, 19(19), 18164-18174.
- Yılmaztürk F., Akçay Ö., 2005. Jpeg Görüntü Sıkıştırmanın Yakın Mesafe Dijital Fotogrametri Üzerindeki Etkileri, s. 918-925, 10. Türkiye Harita Bilimsel ve Teknik Kurultayı, Ankara, Türkiye, 28.03.2005 - 01.04.2005.
There are 22 citations in total.
Details
| Primary Language | English |
|---|---|
| Journal Section | Articles |
| Authors | |
| Publication Date | February 1, 2017 |
| Published in Issue | Year 2017 Volume: 2 Issue: 1 |
