Object detection in very high resolution satellite imagery based on Computer vision techniques

基于计算机视觉技术的超高分辨率卫星图像中的目标检测

• 批准号: 479882-2015
• 负责人: Foucher, Samuel
• 金额: $ 1.82万
• 依托单位: Centre de recherche informatique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=580342
• 关键词: Object; detection; very; resolution; satellite

Huge amounts of data are acquired with either spaceborne or airborne sensors to serve as basis for cartographic data usually being drawn manually. Very high resolution (VHR) aerial and satellite images provide very valuable information. In particular, detecting objects (e.g.: building, cars, boats, etc.) from these images requires a specific consideration, since this information may be used in several remote sensing applications, such as automated map making, urban planning, and land use analysis, etc.. Unfortunately, it is tedious for a human expert to manually label objects in a given aerial or satellite image given the large geographic areas covered with many objects in them which means that analyzing manually the image may take time. Thus, map databases are often outdated. Moreover, in case of crisis situations evoked by, for example, earthquakes or inundations, rapid mapping is essential to organize instant response actions. Therefore, development of robust and fast building object algorithms on VHR aerial and satellite images has become a necessity. Independently, the detection, classification and segmentation of objects in images is a popular subject in computer vision. The goal of this proposal is to review existing methods for object detection in the Compute Vision research area and see their potential applicability to VHR satellite imagery.

大量的数据是通过星载或机载传感器获得的，作为制图的基础。 数据通常是手工绘制的。甚高分辨率（VHR）航空和卫星图像提供了非常 有价值的信息特别地，检测对象（例如：建筑物、汽车、船只等）从这些图像 需要具体考虑，因为这一信息可用于若干遥感应用， 如自动制图、城市规划、土地利用分析等。不幸的是，对于一个 人工专家在给定的大地理区域中手动标记给定航空或卫星图像中的对象 其中覆盖有许多对象，这意味着手动分析图像可能需要时间。因此，Map 数据库经常过时。此外，在地震或其他灾害引发的危机情况下， 在发生洪水时，快速测绘对于组织即时应对行动至关重要。因此，发展稳健 在VHR航空影像和卫星影像上快速建立目标算法已成为必然。独立地， 图像中目标的检测、分类和分割是计算机视觉中的热门课题。的 本文的目的是对计算机视觉研究领域中现有的目标检测方法进行综述 并了解它们对VHR卫星图像的潜在适用性。