A novel method is proposed to automatically extract foreground objects from Martian surface images.The characteristics of Mars images are distinct,e.g.uneven illumination,low contrast between foreground and background,much noise in the background,and foreground objects with irregular shapes.In the context of these characteristics,an image is divided into foreground objects and background information.Homomorphism filtering is first applied to rectify brightness.Then,wavelet transformation enhances contrast and denoises the image.Third,edge detection and active contour are combined to extract contours regardless of the shape of the image.Experimental results show that the method can extract foreground objects from Mars images automatically and accurately,and has many potential applications.
WANG ShuliangLIU ChangWU ShangruNIE QianqianWANG YongtaoZENG ShiZHU Haifeng
Time series motifs are previously unknown,frequently occurring patterns in time series or approximately repeated subsequences that are very similar to each other.There are two issues in time series motifs discovery,the deficiency of the definition of K-motifs given by Lin et al.(2002) and the large computation time for extracting motifs.In this paper,we propose a relatively comprehensive definition of K-motifs to obtain more valuable motifs.Tominimize the computation time as much as possible,we extend the triangular inequality pruning method to avoid unnecessary operations and calculations,and propose an optimized matrix structure to produce the candidate motifs almost immediately.Results of two experiments on three time series datasets show that our motifs discovery algorithm is feasible and efficient.
Lian-hua CHIHe-hua CHIYu-cai FENGShu-liang WANGZhong-sheng CAO
