Automatic building footprint extraction from high-resolution satellite image using mathematical morphology

Abstract

Automatic building extraction from High-Resolution Satellite (HRS) image has been an important field of research in the area of remote sensing. Different techniques related to radiometric, geometric, edge detection and object based have already been discussed and used by various researchers for building extraction. However, faithfulness of extraction is highly dependent on user intervention. This study proposes a novel morphological based automatic approach for extraction of buildings using HRS image. Moreover, using such an automatic approach, buildings can be detected having different size and shape. The proposed technique integrates morphological Top-hat filter, and K-means algorithm to extract buildings having bright and dark rooftops. Further, extracted bright and dark rooftop building segments have been combined together to obtain the final output that contains final extracted building segments. In order to eliminate false-detected buildings, different parameters like area, eccentricity, and axis ratio (major/minor axis) have been used. The suitability of the technique has been judged using different indicators such as completeness, correctness and quality.

A Framework for Automatic Building Detection from Low-Contrast Satellite Images

“…Table 4 presents the experimental findings to distinguish this study with most recent and current studies. Table 4 depicts the quantitative stats to measure quality performance evaluation of the proposed method about the approaches used in the extant literature [63][64][65][66][67][68][69][70]. The results from the prior literature are compared on the basis of commonly used measurement criteria for precision, recall rate, and f -score.…”

Classification of Urban Land Use Based on Graph Theory and Geographic Information System

“…the features of adjacent objects, sub-objects and parent objects). The combined strategy has been applied in various fields, ranging from urban built-up area extraction, building extraction, to land use classification [9][10][11].…”

An investigation in satellite images based on image enhancement techniques

“…Tiede, Baraldi, Sudmanns, Belgiu, and Lang (2017) proposed an architecture and prototypical implementation of a semantic querying system for big earth observation image bases, which enhances the vision of the photographic images. Gavankar and Ghosh (2018) proposed an automatic building foot print extraction from high-resolution satellite image using mathematical morphology. In this approach, buildings can be detected from different size and shapes.…”