Targets based on linear feature often need to be extracted and identified with high precision in the application of photogrammetry. Linear features such as hydrological object boundaries, roads and the boundary of other man made objects are very important for geospatial information extraction and analysis from remotely sensed imagery. This paper deals with subpixel accuracy extraction of linear features, especially specific parallel straight lines. There are many algorithms for localization, such as Gray moment operator, Hough transformation algorithm Forstner operator and so on, just only adopting a single algorithm, the precision of localization is low, and the calculation is complicated. So a new mixed method is proposed in the paper and the procedure can be divided into two steps. Firstly, the rough location of the parallel straight lines was extracted with Hough transformation algorithm. We could get the initial value of parallel straight line in this step. Secondly, straight linear fitting based on Gray moment operator for edge location was adopted to extract the straight lines with high precision. The experimental results indicate that the mixed method for subpixel localization locates the target very validly, and some practicable conclusions are received.