Joon Heo

The image normalization process aims to remove radiometric differences between multitemporal images that are due to nonsurface factors. Accurate normalization is essential for image processing procedures that use multi-date imagery, such as change detection. Linear regression using temporally invariant targets is a widely accepted method for normalization. However, except for the criteria for selecting target points, there is no standard method for conducting this important procedure. This paper

An automated and efficient method for extraction of tunnel cross sections using terrestrial laser scanner (TLS) data is presented. In this process, a three-dimensional (3D) point cloud acquired from the TLS is projected onto a horizon plane, converted to a two-dimensional (2D) planar image, and skeletonized to estimate the tunnel centerline. Stations from which cross sections are extracted are estimated from that centerline, which is vectorized and smoothed for better estimation. From those stat

Automated three-dimensional (3D) modeling of building interiors for an as-built building information model (BIM) incurs critical difficulties because of the complex design of indoor structures and a variety of clutter from scanned point clouds. This paper proposes a scheme for automated 3D geometric modeling of indoor structures, including detailed components such as windows and open doors. Moreover, to produce a regularized model, we imposed constrained least-squares adjustment according to an

In other to save energy, several countries recently made laws related to standby power consumption. To success this exertion, we should consider not only power reduction of consumer electronics itself but also efficient automatic control in networked home environment. In this paper, we present a design approach and implementation result of control mechanism for standby power reduction. Proposed mechanism has the host-agent based structure and uses the IEEE 802.15.4 based ZigBee protocol for comm

The reflectance of the Earth's surface is significantly influenced by atmospheric conditions such as water vapor content and aerosols. Particularly, the absorption and scattering effects become stronger when the target features are non-bright objects, such as in aqueous or vegetated areas. For any remote-sensing approach, atmospheric correction is thus required to minimize those effects and to convert digital number (DN) values to surface reflectance. The main aim of this study was to test the t

Diverse approaches to laser point segmentation have been proposed since the emergence of the laser scanning system. Most of these segmentation techniques, however, suffer from limitations such as sensitivity to the choice of seed points, lack of consideration of the spatial relationships among points, and inefficient performance. In an effort to overcome these drawbacks, this paper proposes a segmentation methodology that: (1) reduces the dimensions of the attribute space; (2) considers the attr

In this study, a parallel processing method using a PC cluster and a virtual grid is proposed for the fast processing of enormous amounts of airborne laser scanning (ALS) data. The method creates a raster digital surface model (DSM) by interpolating point data with inverse distance weighting (IDW), and produces a digital terrain model (DTM) by local minimum filtering of the DSM. To make a consistent comparison of performance between sequential and parallel processing approaches, the means of dea