Abstract
In remote sensing, land cover classification of vegetation and water area from satellite image play a vital role for rural and urban planning and development. Existing algorithms of land cover classification require more sample image datasets for training. For existing algorithms, land cover classification of vegetation and water area is a challenging task because of mixed pixel and geometric distortion over boundary and curvature region. Mixed pixel affects the precise classification and measurement of land cover. Geometric distortion arises due to frame of isotropic and angular selectivity during image acquisition and affects the contour of land cover. In this paper, the proposed transverse dyadic wavelet transform (TDyWT) enhances and classifies vegetation and water area in land cover from LANDSAT image without training datasets. The proposed TDyWT uses Haar wavelet for decomposition and Burt 5 × 7 wavelet for reconstruction. The TDyWT enhances the contour, curvature, and boundary of vegetation and water area in LANDSAT image due to reversible and lifting properties of wavelet. TDyWT removes geometric distortion and spatial scale error of mixed pixel. In traditional land surveying spatial scale error reduction eliminates through total station and error modeling techniques. From the results, the proposed TDyWT algorithm classifies the area of subclass of vegetation and water with the 95% of accuracy with respect to ground truth survey methods.
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Arqub OA, Abo-Hammour Z (2014) Numerical solution of systems of second-order boundary value problems using continuous genetic algorithm. Inf Sci 279:396–415
Arqub OA, Al-Smadi M, Momani S, Hayat T (2016) Numerical solutions of fuzzy differential equations using reproducing kernel Hilbert space method. Soft Comput 20(8):3283–3302
Arqub OA, Al-Smadi M, Momani S, Hayat T (2017) Application of reproducing kernel algorithm for solving second-order, two-point fuzzy boundary value problems. Soft Comput 21:7191–7206
Awrangjeb M, Fraser CS (2014) An automatic and threshold-free performance evaluation system for building extraction techniques from Airborne LIDAR data. IEEE J Sel Top Appl Earth Observ Remote Sens 7(10):4184–4198
Blaschke T, Feizizadeh B, Helbling D (2014) Object-based image analysis and digital terrain analysis for locating landslides in the Urmia Lake Basin, Iran. IEEE J Sel Top Appl Earth Observ Remote Sens 7(12):4806–4817
Bruzzone L, Carlin L (2006) A multilevel context-based system for classification of very high spatial resolution Images. IEEE Trans Geosci Remote Sens 44(9):2587–2600
Demirel H, Anbarjafari G (2010) Satellite image resolution enhancement using complex wavelet transform. IEEE Geosci Remote Sens Lett 7(1):123–126
Deng W, Zhao H, Zou L et al (2017a) A novel collaborative optimization algorithm in solving complex optimization problems. Soft Comput 21:4387–4398
Deng W, Zhao H, Yang X, Xiong J, Sun M, Li B (2017b) Study on improved adaptive PSO algorithm for solving multi-objective gate assignment. Appl Soft Comput 59:288–302
Deng W, Xu J, Zhao H (2019) An improved ant colony optimization algorithm based on hybrid strategies for scheduling problem. IEEE Access 7:20281–20292
Fan J, Chen T, Lu S (2015) Vegetation coverage detection from very high-resolution satellite imagery. In: 2015 Visual communications and image processing (VCIP), pp 1–4, 13–16 Dec 2015
Harbas I, Subasic M (2014) Detection of roadside vegetation using features from the visible spectrum. In: MIPRO 2014, Opatija, Croatia, pp 1204–1209, 26–30 May 2014
Iovan C, Boldo D, Cord M (2008) Detection, characterization, and modeling vegetation in urban areas from high-resolution aerial imagery. IEEE J Sel Top Appl Earth Observ Remote Sens 1(3):206–213
Lindberg E, Eysn L, Hollaus M, Holmgren J, Pfeifer N (2014) Delineation of tree crowns and tree species classification from full-waveform airborne laser scanning data using 3-D ellipsoidal clustering. IEEE J Sel Top Appl Earth Observ Remote Sens 7(7):3174–3181
Long Z, He M, Shi H, Rao R (2009) Study on water bodies extraction with FY3A satellite image. In: 2nd International congress on image and signal processing, 2009. CISP ‘09, pp 1–5, 17–19 Oct 2009
McInnes WS, Smith B, McDermid GJ (2015) Discriminating native and nonnative grasses in the dry mixedgrass prairie with MODIS NDVI time series. IEEE J Sel Top Appl Earth Observ Remote Sens 8(4):1395–1403
Nageswari CS, Prabha KH (2018) Preserving the border and curvature of fetal heart chambers through TDyWT perspective geometry wrap segmentation. Multimed Tools Appl 77(8):10235–10250
Pal M, Mather PM (2005) Support vector machines for classification in remote sensing. Int J Remote Sens 26(5):1007–1011
Paris C, Valduga D, Bruzzone L (2016) A hierarchical approach to three-dimensional segmentation of LiDAR data at single-tree level in a multilayered forest. IEEE Trans Geo Sci Remote Sens 54(7):4190–4203
Petrou ZI, Manakos I, Stathaki T, Mücher CA, Adamo M (2015) Discrimination of vegetation height categories with passive satellite sensor imagery using texture analysis. IEEE J Sel Top Appl Earth Observ Remote Sens 8(4):1442–1455
Shi H, Chen L, Bi F, Chen H, Yu Y (2015) Accurate urban area detection in remote sensing images. IEEE Geosci Remote Sens Lett 12(9):1948–1952
Singh K, Ghosh M, Sharma SR (2016) WSB-DA: water surface boundary detection algorithm using LANDSAT 8 OLI data. IEEE J Sel Top Appl Earth Observ Remote Sens 9(1):363–368
Sirmacek B, Unsalan C (2009) Urban-area and building detection using SIFT keypoints and graph theory. IEEE Trans Geosci Remote Sens 47(4):1156–1167
Sirmacek B, Unsalan C (2010) Urban area detection using local feature points and spatial voting. IEEE Geosci Remote Sens Lett 7(1):146–150
Wang Z, Boesch R (2007) Color- and texture-based image segmentation for improved forest delineation. IEEE Trans Geo Sci Remote Sens 45(10):3055–3062
Xie J, Jiang Y, Tsui H-T, Heng P-A (2006) Boundary enhancement and speckle reduction for ultrasound images via salient structure extraction. IEEE Trans Biomed Eng 53(11):2300–2309
Zarea A, Mohammadzadeh A (2016) A novel building and tree detection method From LiDAR data and aerial images. IEEE J Sel Top Appl Earth Observ Remote Sens 9(5):1864–1875
Zeng C, Wang J, Huang X, Bird S, Luce JJ (2015) Urban water body detection from the combination of high-resolution optical and SAR images. In: Joint urban remote sensing event (JURSE), pp 1–4
Zhan Z, Lai B (2012) Vegetation detection of close-range images for landslide monitoring. In: International conference on computer vision in remote sensing (CVRS), pp 13–18, 16–18 Dec 2012
Zhao H, Zheng J, Xu J, Deng W (2019a) Fault diagnosis method based on principal component analysis and broad learning system. IEEE Access 7:99263–99272
Zhao H, Liu H, Xu J, Deng W (2019) Performance prediction using high-order differential mathematical morphology gradient spectrum entropy and extreme learning machine. In: IEEE transations on instrumentation measurement. IEEE, pp 1–1. https://doi.org/10.1109/TIM.2019.2948414
Zhu H, Barish M, Pickhardt P, Liang Z (2013) Haustral fold segmentation with curvature-guided level set evolution. IEEE Trans Biomed Eng 60(2):321–331
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Prabu, M., Shanker, N.R., Celine Kavida, A. et al. Geometric distortion and mixed pixel elimination via TDYWT image enhancement for precise spatial measurement to avoid land survey error modeling. Soft Comput 24, 14687–14705 (2020). https://doi.org/10.1007/s00500-020-04814-x
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DOI: https://doi.org/10.1007/s00500-020-04814-x