Broad Neural Network for Change Detection in Aerial Images
A change detection system takes as input two images of a region captured at two different times, and predicts which pixels in the region have undergone change over the time period. Since pixel-based analysis can be erroneous due to noise, illumination difference and other factors, contextual information is usually used to determine the class of a pixel (changed or not). This contextual information is taken into account by considering a pixel of the difference image along with its neighborhood. With the help of ground truth information, the labeled patterns are generated. Finally, Broad Learning classifier is used to get prediction about the class of each pixel. Results show that Broad Learning can classify the data set with a significantly higher F-Score than that of Multilayer Perceptron. Performance comparison has also been made with other popular classifiers, namely Multilayer Perceptron and Random Forest.
Code (0)
등록된 구현이 없습니다.
Tasks
Change DetectionSimilar Papers 제목 키워드 기반
Semantic Change Pattern Analysis
Change detection is an important problem in vision field, especially for aerial images. However, most works focus on traditional change detection, i.e., where changes happen, without considering the change type informati…
Change DetectionUnsupervised Self-training Algorithm Based on Deep Learning for Optical Aerial Images Change Detection
Optical aerial images change detection is an important task in earth observation and has been extensively investigated in the past few decades. Generally, the supervised change detection methods with superior performance…
Change DetectionEarth ObservationRefAerial: A Benchmark and Approach for Referring Detection in Aerial Images
Referring detection refers to locate the target referred by natural languages, which has recently attracted growing research interests. However, existing datasets are limited to ground images with large object centered i…
RelationRS: Relationship Representation Network for Object Detection in Aerial Images
Object detection is a basic and important task in the field of aerial image processing and has gained much attention in computer vision. However, previous aerial image object detection approaches have insufficient use of…
Objectobject-detectionObject DetectionObject Detection In Aerial ImagesDetecting Building Changes with Off-Nadir Aerial Images
The tilted viewing nature of the off-nadir aerial images brings severe challenges to the building change detection (BCD) problem: the mismatch of the nearby buildings and the semantic ambiguity of the building facades. T…
Building change detection for remote sensing imagesChange Detection