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http://dx.doi.org/10.9717/kmms.2016.19.4.725

Automatic National Image Interpretability Rating Scales (NIIRS) Measurement Algorithm for Satellite Images  

Kim, Jeahee (Dept. of Radio & Information Communications Eng., Chungnam National University)
Lee, Changu (Dept. of Radio & Information Communications Eng., Chungnam National University)
Park, Jong Won (Dept. of Radio & Information Communications Eng., Chungnam National University)
Publication Information
Abstract
High-resolution satellite images are used in the fields of mapping, natural disaster forecasting, agriculture, ocean-based industries, infrastructure, and environment, and there is a progressive increase in the development and demand for the applications of high-resolution satellite images. Users of the satellite images desire accurate quality of the provided satellite images. Moreover, the distinguishability of each image captured by an actual satellite varies according to the atmospheric environment and solar angle at the captured region, the satellite velocity and capture angle, and the system noise. Hence , NIIRS must be measured for all captured images. There is a significant deficiency in professional human resources and time resources available to measure the NIIRS of few hundred images that are transmitted daily. Currently, NIIRS is measured every few months or even few years to assess the aging of the satellite as well as to verify and calibrate it [3]. Therefore, we develop an algorithm that can measure the national image interpretability rating scales (NIIRS) of a typical satellite image rather than an artificial target satellite image, in order to automatically assess its quality. In this study, the criteria for automatic edge region extraction are derived based on the previous works on manual edge region extraction [4][5], and consequently, we propose an algorithm that can extract the edge region. Moreover, RER and H are calculated from the extracted edge region for automatic edge region extraction. The average NIIRS value was measured to be 3.6342±0.15321 (2 standard deviations) from the automatic measurement experiment on a typical satellite image, which is similar to the result extracted from the artificial target.
Keywords
Image Processing; Satellite Imagery; Remote Sensing;
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  • Reference
1 IRARS Committee, http://www.fas.org/irp/imint/niirs_c/index.html (accessed Dec., 10, 2015).
2 J. Leachtenauer, W. Malila, J. Irvine, L.Colburn, and N. Salvaggio, "General Image-Quality Equation: GIQE," Journal of Applied Optics, Vol. 36, No. 32, pp. 8322-8328, 1997.   DOI
3 Image Quality Evaluation of Quickbird Super Resolution and Revisit of IKONOS : Civil and Commercial Application Project, JACIE, http://calval.cr.usgs.gov/JACIE_files/JACIE04/files/1Jones12.pdf (accessed Dec., 10, 2015).
4 H.S. Kim, Research for the Automatic Rating of Satellite Image Interpretability, Master's Thesis of Inha University of Geographic Information Engineering Department, 2008.
5 T. Kim, J. Kim, D. Kim, and J. Jeong, "Automated Image Interpretability Assessment by Edge Profile Analysis of Natural Targets," Proceeding of Annual Conference, American Society for Photogrammetry and Remote Sensing, pp. 417-422, 2010.
6 L. Lin, H. Luo, and H. Zhu, "Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data," Journal of Remote Sensing, Vol. 6, pp. 4409-4429, 2014.   DOI
7 R. Ryan, B. Baldridge, R.A. Schowengerdt, T. Choi, D. Helder, S. Blonsk, "IKONOS Spatial Resolution and Image Interpretability Characterization," Journal of Remote Sensing of Environment, Vol. 88, pp. 37-52, 2014.   DOI
8 K. Kohm, "Modulation Transfer Function Measurement Method and Results for the Orbview-3 High Resolution Imaging Satellite," Proceeding of International Society for Photogrammetry and Remote Sensing, pp. 7-12, 2004.
9 U.M. Leloglu and E. Tunali, "On-orbit Modulation Transfer Function Estimation for BiLSAT Imagers," Proceeding of International Society for Photogrammetry and Remote Sensing, pp. 45-51, 2006.
10 M. Crespi and L.D. Vendictis, "A Procedure for High Resolution Satellite Imagery Quality Assessment," Sensors, Vol. 9, No. 5, pp. 3289-3313, 2009.   DOI
11 R.O. Duda and P.E. Hart, "Use of the Hough Transformation to Detect Lines and Curves in Pictures," Journal of Communications of the Assoclation for Computing Machinery, Vol. 15, No. 1, pp. 11-15, 1972.   DOI
12 P.D. Burns, "Slanted-edge MTF for Digital Camera and Scanner Analysis," Proceeding of Image Processing, Image Quality, Image Capture, Systems Conference, pp. 135-138, 2000.
13 D. Williams, "Benchmarking of the ISO 12233 slanted-edge Spatial Frequency Response Plug-in," Proceeding of Image Processing, Image Quality, Image Capture, Systems Conference, pp. 133-136, 1998.
14 S.S Bae, H.C. Kim, K.S. Kim, H.Y. Park, C.S. Cho, "A Development on The 3D Terrain Map Creator Editor using Satellite Image and Geographic Informatio," Journal of Korea Multimedia Society, Vol. 15, No. 1, pp. 147-150, 2012.