An approach to extracting information of residential areas from Beijing-1 image based on Gabor texture segmentation

According to the features of high-resolution panchromatic imagery of Beijing-1 small satellite,an approach to extracting information of residential areas is proposed in this paper based on Gabor texture segmentation.The algorithm extracts the features in different directions and different scales by building the Gabor filter,uses cluster analysis of multiple features to segment the image,and performs the fusion processing based on morphological scale space.It solves the problems in image processing resulting from low contrast between remote sensing objects and background,the blurring of image edges and high noise.It has the benefits of direction selection and frequency selection with strong self-adaptive ability.Our experiments prove the effectiveness of the approach for extracting information of residential areas from Beijing-1 high-resolution imagery.

Multi-Phase Texture Segmentation Using Gabor Features Histograms Based on Wasserstein Distance

We present a multi-phase image segmentation method based on the histogram of the Gabor feature space,which consists of a set of Gabor-filter responses with various orientations,scales and frequencies.Our model replaces the error function term in the original fuzzy region competition model with squared 2-Wasserstein distance function,which is a metric to measure the distance of two histograms.The energy functional is minimized by alternative minimization method and the existence of closed-form solutions is guaranteed when the exponent of the fuzzy membership term being 1 or 2.We test our model on both simple synthetic texture images and complex natural images with two or more phases.Experimental results are shown and compared to other recent results.

Segmentation of Visual Images by Sequential Extracting Homogeneous Texture Areas

The purpose of the research is to develop a universal algorithm for partial texture segmentation of any visual images. The main peculiarity of the proposed segmentation procedure is the extraction of only homogeneous fine-grained texture segments present in the images. At first, an initial seed point is found for the largest and most homogeneous segment of the image. This initial seed point of the segment is expanded using a region growing method. Other texture segments of the image are extracted analogously in turn. At the second stage, the procedure of merging the extracted segments belonging to the same texture class is performed. Then, the detected texture segments are input to a neural network with competitive layers which accomplishes more accurate delineation of the shapes of the extracted texture segments. The proposed segmentation procedure is fully unsupervised, i.e., it does not use any a priori knowledge on either the type of textures or the number of texture segments in the image. The research results in development of the segmentation algorithm realized as a computer program tested in a series of experiments that demonstrate its efficiency on grayscale natural scenes.

Tectonic boundaries in the South China Sea from aeromagnetic signature

Magnetic data has been widely applied in the tectonic division.High-resolution magnetic data were used to analyze the geotectonic zoning of the South China Sea.Based on the newly compilated magnetic data,the processing results and the distribution of known faults,we consider that the U-shaped line approximately along the South China Sea national boundary of China shown in the magnetic map is a significant geological and geophysical boundary.We first described the linear characteristics of the magnetic data and then applied pseudo-gravity,Euler deconvolution,tilt derivatives,and the texture segmentation method to process the data.Results show that the dividing line between the South China Sea and the surrounding blocks is approximately along this U-shaped line.The dividing line between the South China domain and the South China Sea domain is along with the Dongsha Islands to Xisha Trough,which is different from the previous geophysical zoning results.Our results are almost consistent with those of the gravity data indicating roughly the tectonic zonation along the U-shaped line.

Boundary-aware texture region segmentation from manga

Due to the lack of color in manga(Japanese comics), black-and-white textures are often used to enrich visual experience. With the rising need to digitize manga, segmenting texture regions from manga has become an indispensable basis for almost all manga processing, from vectorization to colorization. Unfortunately, such texture segmentation is not easy since textures in manga are composed of lines and exhibit similar features to structural lines(contour lines). So currently, texture segmentation is still manually performed, which is labor-intensive and time-consuming. To extract a texture region, various texture features have been proposed for measuring texture similarity, but precise boundaries cannot be achieved since boundary pixels exhibit different features from inner pixels. In this paper, we propose a novel method which also adopts texture features to estimate texture regions. Unlike existing methods, the estimated texture region is only regarded an initial, imprecise texture region. We expand the initial texture region to the precise boundary based on local smoothness via a graph-cut formulation. This allows our method to extract texture regions with precise boundaries. We have applied our method to various manga images and satisfactory results were achieved in all cases.