Edge extraction from high spatial resolution (HSR) remotely sensed images is one of the essential tasks for image segmentation and object identification. We present an optimal Gabor-based edge detection method which mainly focuses on selecting optimal parameters, including central frequency and spectrum scale, for Gabor filter. The central frequency is automatically optimized by phase randomization and the human visual system-based structure similarity index. Next, the optimal spectrum scale is determined based on two-dimensional power spectrum density. The edge detection method is comprehensively discussed in the analysis of parameter sensitivity, overall performance, and comparative tests with several widely used methods. Qualitative and quantitative experimental studies, performed on six test images with various spatial resolution, show that the proposed method provides a promising solution to edge detection from HSR remotely sensed images.
In this paper a method of Fourier spectrum features based edge detection of urban street trees is described. The QuickBird image was first transformed by 2-D discrete Fourier transform. Then the energy of the component in spatial frequency was calculated. The energy distribution of the angle in max energy was used for further study. Different frequency segments was analyzed, the frequency that can best describe the street tree edge was chosen as the cut-off frequency of the street trees edge. Odd Gabor filter in frequency domain with the cut-off frequency and the max-energy angle was applied for the edge detection. The road center line is extracted by a Gabor filter in frequency domain. Then the edge of the street trees is restricted by the road center line. The edge detection result is analyzed by Canny criteria, and the ΣV=1.00, and C=0.89.
A method of texture analysis and feature extraction of urban street trees in spatial frequency domain is described in this
paper. The QUICKBIRD image of Nanjing acquired in July, 2007 was considered. The image was first transformed by
2-D discrete Fourier transform. Then the energy of the component in spatial frequency was calculated. Entropy in a
region of 7x7 window was considered to evaluate the energy distribution of the image. A Gabor filter was designed to
extract texture features of street trees by using the radius and angel information of the entropy image. The precision of
the segmentation result is 79.96%. Odd Gabor filter was designed to detect the edge of street trees, and the experimental
result is excellent.