Total views : 99
An Empirical Study on the Influence of Image Filters in Effective Closed Contour Extraction of Lakes in Satellite Images
Objectives: The water contour extraction models using satellite images could be highly useful in monitoring the long term changes in river tributaries, lakes and other coastal areas. The lakes are termed for a localized basin of varied size where the water from river tributaries got reserved. These lakes are one among the prime source of water consumption for human needs. Hence, change monitoring in water levels of lakes is a highly needed measure for sustainability. Methods/Statistical Analysis: Though use of bathymetry and elevation data can aid the coastal monitoring models, a simple automated closed contour extraction model can support shape based change monitoring or satellite image based water volume assessment models. In general, the contour extraction of lakes or any water bodies is relatively difficult when compared with urban structures from spatial data. It is due to the indefinite shape of water bodies on varying levels of water. The use of image filters to improve the power of boundary discrimination is inevitable. However, it may also deteriorate the image quality leading to loss of information. Hence, the proposed model has examined the influence of widely used image filters both for smoothening and sharpening with respect to satellite image on applying suitable image quality assessment metrics. Findings: On the empirical analysis of the chosen image filters, the Adaptive wiener and Gaussian filters are found to be the more effective sharpening and smoothening filters respectively for satellite images. Further, the outstanding image filters found on evaluation is combined with local thresholding; shape based filtering and morphological operations in a sequence to extract an effective closed contour of water bodies. Applications: The proposed model can be applied for satellite image preprocessing for effective noise suppression and edge preservation. The closed contour extraction can be applied with change detection based applications for satellite images.
Contour Extraction, Image Filter, Lake, Preprocessing, Satellite Image.
- Gecen R, Sarp G. Road Detection from High andLow Resolution Satellite Images.ISPRS - Archives. 2008,37 (B4):355-58.
- Bernabe S, Plaza A, Marpu PR, Benediktsson JA. A new parallel tool for classification of remotely sensed imagery. Computers and Geosciences. 2012; 46:208–18. https://doi.org/10.1016/j.cageo.2011.12.009
- Mallinis G, Koutsias N, Tsakiri-Strati M,Karteris M. Object based classification using Quickbird imagery for delineating forest vegetation polygons in a Mediterranean test site. ISPRS Journal of Photogrammetry and Remote Sensing. 2008; 63(2):237-50. https://doi.org/10.1016/j.isprsjprs.2007.08.007
- Xiaohong X,Yonggang W. A cloud-removal method based on image fusion using local indexes. Computer Modelling & New Technologies. 2014; 18(4):82-88.
- Weng Q, Lu D,Schubring J. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment. 2004, 89(4):467-83. https://doi.org/10.1016/j.rse.2003.11.005
- MakandarA, Hallali B. Image Enhancement techniques usingHighpass and Low pass filters. International Journal of Computer Applications. 2015; 109(14):12-15.
- Rakshit S, Ghosh A, Shankar BU. Fast mean Filtering Technique. Pattern Recognition. 2007; 40:890-97. https:// doi.org/10.1016/j.patcog.2006.02.008
- Praveena S, Singh SP. Hybrid Clustering Algorithm and Feed-Forward Neural Network for Satellite Image Classification. International Journal of Engineering Science Invention. 2014; 3(1):39-47.
- RamanjaneyuluK, RahimBA,Shaik F. Effect of Wavelet Based Compression Methods on Enhanced Medical Imagery. International Journal of Advanced Research in Computer Science and Software Engineering. 2013; 3(9):113-17.
- Bhandari AK, Kumar A, Singh GK. Improved knee transfer function and gamma correction based method for contrast and brightness enhancement of satellite image. International Journal of Electronics and Communications. 2015; 69(2)579–89. https://doi.org/10.1016/j.aeue.2014.11.012
- Singh RP, Dixit M. Histogram Equalization Techniques forImage Enhancement.International Journal of Signal Processing, Image Processing and Pattern Recognition. 2015; 8(8):345-52. https://doi.org/10.14257/ijsip.2015.8.8.35
- Rassoul A,Mahiny S, Brian J, Turner. A Comparison of Four Common Atmospheric Correction Methods. Photogrammetric Engineering & Remote Sensing. 2007; 4:361-68.
- Rokni K, Ahmad A, Selamat A,Hazini S. Water Feature Extraction and Change Detection using Multitemporal Landsat Imagery. Remote Sensing. 2014; 6(5):4173-89. https://doi.org/10.3390/rs6054173
- Du Y, Zhang Y, Ling F, Wang Q, Li W, Li X. Water Bodies’ Mapping from Sentinel-2 Imagery with Modified Normalized Water Index at 10-m Spatial Resolution Produced by Sharpening the SWIR Band. Remote Sensing. 2016; 8(4):354. https://doi.org/10.3390/rs8040354
- Datir KS, Shinde JV. Neighborhood Window Pixelingfor Document Image Enhancement. International Journal of Computer Applications. 2016; 146(12):12-17. https://doi.org/10.5120/ijca2016910925
- Sayyed N, Joshi P,Wagh C. Novel Approaches of Image Segmentation for Water Bodies Extraction. International Journal of Advancement in Engineering Technology, Management and Applied Science. 2015; 2(2):40-6.
- Singh OI,Sinam T, James O, Singh TR. Local contrast and Mean based Thresholding Technique in Image Binarization. International Journal of Computer Applications. 2012; 51(6): 6-10.
- Hahmann T, Vessel B. Surface Water Body Detection in TerraSAR-X Data using Active Contour Models. European Conference on Synthetic Aperture Radar.2010.
- Airouche M, Bentabet L,Zelmat M. Image Segmentation Using Active Contour Model and Level Set Method Applied to Detect Oil Spills. Proceedings of the World Congress on Engineering. 2009.
- Hong S, Jang H, Kim N, Sohn H. Water Area Extraction using RADARSAT SAR Imagery Combined with
- Landsat Imagery and Terrain Information. Sensors. 2015; 15(3):6652-67. https://doi.org/10.3390/s150306652 PMid:25808768 PMCid:PMC4435168
- Smart GM, Bind J, Duncan MJ. River bathymetry from conventional LiDAR using Water Surface Returns.18th World IMACS / MODSIM Congress. 2009; p.2521-27.
- Kodge BG, Hiremath PS. Elevation Contour Analysis and Water Body Extraction for Finding Water Scarcity Locations using DEM. World Journal of Science and Technology. 2011; 1(12):29-34.
- Mary MCVS, Rajsingh EE, Jacob JKK, Anandhi D, Amato U,Selvan SE. An empirical study on optic disc segmenta tion using an active contour model. Biomedical Signal Processing and Control. 2015; 18:19-29. https://doi.org/10.1016/j.bspc.2014.11.003
- Jiang H, Feng M, Zhu Y, Lu N, Huang J, Xiao T. An Automated Method for Extracting Rivers and Lakes from Landsat Imagery. Remote Sensing. 2014; 6(6):5067-89. https://doi.org/10.3390/rs6065067
- Lu D, Mausel P, Brondizio E, Moran E. Assessment of Atmospheric Correction Methods for Landsat TM Data Applicable to Amazon Basin LBA Research. InternationalJournal of Remote Sensing. 2002; 23(13):265171. https://doi.org/10.1080/01431160110109642
- Landsat 8 Band details. Date Accessed:September 2016. Available from:http:blogs.esri.com/esri/arcgis/2013/07/24/ band-combinations-for-landsat-8/
- Anutam, Rajni. Comparative Analysis of Filters and Wavelet based Thresholding Methods for Image Denoising. Computer Science & Information Technology. 2014; p.13748. https://doi.org/10.5121/csit.2014.4515
- Image Restoration- Lecture notes. Date Accessed: November 2016. Available from: https://www8.cs.umu.se/ kurser/TDBC30/VT05/material/lecture5.pdf.
- Hoshyar AN, Al-Jumailya A,Hoshyar AN. Comparing the Performance of Various Filters on Skin Cancer Images. Procedia Computer Science. 2014; 42:32-7. https://doi.org/10.1016/j.procs.2014.11.030
- Paul OI, LuY. Image Denoising Using Wavelet Thresholding Techniques.International Journal of Education and Research. 2014; 2(2):1-5.
- Hassan M,Bhagvati C. Structural Similarity Measure for Color Images. International Journal of Computer Applications. 2012; 43(14):7-12. https://doi.org/10.5120/6169-8590
- Krupnik A, Elder JH. Extraction of Lakes from Satellite Imagery. Symposium on Geospatial Theory, Processing and Applications. 2002. PMid:11969093
- Garg R, Mittal B, Garg S. Histogram Equalization Techniques forImage Enhancement. International Journal of Electronics andCommunication Technology. 2011; 2(1):107-11.
- Bhandari AK, Kumar A, Singh GK. Improved knee transfer function and gamma correction based method for contrast and brightness enhancement of satellite image. International Journal of Electronics and Communications. 2015; 69(2):579-89. https://doi.org/10.1016/j.aeue.2014.11.012
- Thamman P, Bhatia R. A New Methodology for Improvement of Contrast to Show Fractures in X-ray Images. International JournalComputer Science and Information Technologies. 2014; 5(5):6400-03.
- Bernsen local image Thresholding. Date Accessed: October 2016. Available from: https://in.mathworks.com/ matlabcentral/fileexchange/40856-bernsen-local-imagethresholding.
- Liu H, Jezek JC. Automated extraction of coastline from satellite imagery by integrating canny edge detection and locally adaptive thresholding methods. InternationalJournal of Remote Sensing. 2004; 25(5):937-58. https://doi.org/10.1080/0143116031000139890
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.