However, it is hard to define the reasonable ��energy�� function for each image. Angular texture signature (ATS) has also been improved to semi-automatically track road axes. Lin et al. [28] and Shen et al. [29] proposed the mean value and the entropy besides existing variance to measure the texture. As a result, ATS is capable of tracing the bright ribbon roads from SPOT imagery or tracing the dark ribbon roads from VHR COSMO SAR imagery. Minimum cost to follow a path was proposed by Shukla et al. [30]. Essentially, the minimum cost is similar to the ATS in the sense that it takes variance as a measure of texture. Another practical methodology is template matching. McKeown and Denlinger [31] introduced a semi-automatic road tracker based on profile correlations. This road tracker starts from some road seed points.

The profile matching technique compares a reference profile with the road profile at a pixel predicted to be on the road. The differences between the two profiles are measured by identifying two geometric parameters (shift and width) and two radiometric parameters (brightness and contrast). These parameters are estimated by minimizing the squared sum of the gray value differences between the profiles. Actually, the subsequent approaches essentially follow the same scheme as the above method. Vosselman and Knecht [1] improved the profile matching with a Kalman filter, Baumgartner et al. [25] also developed a human-computer interactive prototype system based on the above method. Zhou et al.

[32] used two profiles, one orthogonal to the road direction and the other parallel to the road direction, to enhance the robustness of the tracker and applied extended Kalman filter and particle filter to solve profile matching problems Carfilzomib for road tracking, and a prototype system for semi-automatic road extraction is also developed. Kim et al. [33] utilized a rectangular template instead of profile to track ribbon roads by least squares template matching from VHR satellite images. Zhao et al. [34] used rectangular template matching on the classified imagery and proposed another prototype. However, there are no reports on their applicability on VHR images finer than 0.2 m/pixel, and most of the road trackers mentioned above don’t operate well when they encounter irregular geometric deformations and radiometric changes due to the appearance of road junctions, material changes, occlusion from cars, shadows, lane markings etc. As a result, consecutive failure of the road tracker not only loses efficiency, but also increases the work required of the human operators.After reviewing the existing work on road extraction, it was realized that ATS, profile matching and rectangular template matching are practical to extract road networks.