A Semi Automatic Road Extraction Method for Alos Satellite Imagery

A semi automatic road extraction method has been constructed and evaluated. Our purpose is to obtain 1/25,000 level road data from PRISM image. PRISM is panchromatic, three views, and the 2.5m resolution sensor carried on ALOS satellite that will be launched on late 2004. A centre line-detecting algorithm is employed for feature extraction. It picks up pixels where second derivative of brightness becomes maximal. Then those pixels are linked if both probability of line and angle difference between adjacent pixels satisfy given conditions. Acquired line candidates are classified by its photometric property. We test both automatic grey scale threshold method and traditional unsupervised multi band classification method for this stage. After eliminating false line segments, a line linking method is applied. If all of angle difference, lateral offset, and net gap are less than threshold, the pair is considered as one long line. This process is applied iteratively while a connectable pair remains. The proposed method was tested by a simulated ALOS image data set created from three-line airborne sensor images and an IKONOS data set. The result shows that 80% of road was extracted before false line elimination while 80% of extracted line was false data. There still remains 70% of false road segments even after the classification method. Both correctness and completeness are unexpectedly poor. As our method is working on a single image and does not use full feature of PRISM yet, a method using three-dimensional property is needed.