Extracting buildings in a satellite image is of paramount important for urban planning, detecting changes of landscape and analysis. Extracting building in the satellite image is complex as its micro features are difficult to infer on the image. Feature extraction techniques readily available to extract the built up areas. In this paper, the five feature extraction techniques which include edge detection, grey scale morphological operation, haralick texture extraction, morphological classification and local statistics methods are introduced and compared. The satellite image is registered and geometric correction has performed for further processing. The image is applied with filtering algorithm to remove noises and then these five feature extraction algorithms are applied with the image. The results are more promising and the buildings are extracted from the test images.
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Konstantinidis D, Stathaki T (2017) Building detection using enhanced HOG–LBP features and region refinement processes. IEEE J Sel Top Appl Earth Obs Remote Sens 10(3):888–905CrossRefGoogle Scholar
Huang X (2017) A new building extraction postprocessing framework for high-spatial-resolution remote-sensing imagery. IEEE J Sel Top Appl Earth Obs Remote Sens 10(2):654–668CrossRefGoogle Scholar
Manandhar P, Aung Z, Marpu PR (2017) Segmentation based building detection in high resolution satellite images. IEEE international geoscience and remote sensing symposium (IGARSS), pp 3783–3786Google Scholar
Partovi T, Bahmanyar R, Krauß T, Reinartz P (2017) Building outline extraction using a heuristic approach based on generalization of line segments. IEEE J Sel Top Appl Earth Obs Remote Sens 10(3):933–947CrossRefGoogle Scholar
Du S, Zhang Y, Zou Z, Xu S, He X, Chen S (2017) Automatic building extraction from LiDAR data fusion of point and grid-based features. ISPRS J Photogrammetry Remote Sens 130:294–307CrossRefGoogle Scholar
Xia S, Wang R (2018) Extraction of residential building instances in suburban areas from mobile LiDAR data. ISPRS J Photogrammetry Remote Sens 144:453–468CrossRefGoogle Scholar
Alshehhi R, Marpu PR, Woon WL, Dalla Mura M (2017) Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks. ISPRS J Photogrammetry Remote Sens 130:139–149CrossRefGoogle Scholar
Turker M, Koc-San D (2015) Building extraction from high-resolution optical spaceborne images using the integration of support vector machine (SVM) classification, Hough transformation and perceptual grouping. Int J Appl Earth Obs Geoinf 34:58–69CrossRefGoogle Scholar
Haralick RM, Shanmugam K et al (1973) Textural features for image classification. IEEE Trans Systems, Man, Cybern 6:610–621CrossRefGoogle Scholar
Pesaresi M, Benediktsson JA (2001) A new approach for the morphological segmentation of high resolution satellite imagery. IEEE Trans Geosci Remote Sens 39(2):309–320CrossRefGoogle Scholar