This paper proposes an automatic method to compute the exposure time for space array Charge Coupled Device(CCD) based on image quality. An imaging simulation for geostationary satellite array CCD camera is designed. The range of normal exposure time is calculated according to the modified exposure estimation method. The exact exposure time can be automatically obtained based on selected image quality evaluation indexes for any given location and time. Experimental results confirm that the proposed algorithm is effective and leads to improvement in photography to obtain high quality remote sensing images.
The gray level difference between the pedestrians and environment is small in infrared images, and it is easy to appear the problem of fault segmentation while segmenting. This paper proposes a dual-threshold segmentation method for infrared pedestrian. The global threshold of the image is computed by using the statistical variance, and it is used for a preliminary segmentation. A cross-shaped sliding window is introduced to scan the image. The local threshold of each pixel in the initial segmentation objective area is computed by using statistical variance. By means of the classified formula, the pixel can be classified into objects or the background area. The binary image is obtained. Experiments show that this method improves the segmentation accuracy, and has good performance on pedestrian segmentation.
This paper studies the optimal information rate of perfect secret sharing schemes of a type of access structures on seven participants. Based on the relationship between these access structures and their connected graphs, 111 connected graphs corresponding to these access structures are given. The exact values of the optimal information rate of 91 access structures based on graphs are computed and the secret sharing schemes attaining the optimal information rate are discussed in Table 1, where the upper and lower bounds on the information rate of the rest 20 are also calculated. The upper bound on the information rate of connected graphs on seven vertices is theoretically proved.
Through the analysis of the Distributed Denial of Service(DDoS) attack characteristics and the entropy changes of data flow five-tuple during the attacks, this paper proposes a detection model based on data Flow Struct Stability(FSS). This method through AR autoregression model to estimate multi-dimensional characteristic parameter of FSS time series, then classifies Support Vector Machine(SVM) with sample training into several categories and uses these results to identify the attacks. Experiments show that the model has high detection quality.
The time complexity of the Parzen Window(PW) based Mean Shift Spectral Clustering(MSSC) algorithm is not less than O(N2), which means that it is impractical for medical image segmentation. In is paper, the problem of heavy time cost of original MSSC is solved by using two strategies of data condensation: reduced set density estimator and random sampling from every attraction basin, and the novel Data Condensation Based Spectral Clustering(DCBSC) algorithm is proposed. Compared with MSSC, the time cost of DCBSC is decreased effectively, and the practicability of DCBSC for medical image segmentation is improved accordingly.
To solve the difficulty of identifying encrypted traffic, this paper proposes a fast network traffic identification method, which applies traffic payload signatures extraction instead of the deep analysis of full-payload data. This method uses 256-dimensional vector to describe the frequency of the packet payload 256 ASCII bytes occur. It extracts payload signatures based on the mean and variance of the quantitative traffic payload. Then it classifies the network traffic into different applications by using a decision tree model. Experimental results show the proposed method can accurately classify the common encrypted network traffic and detect traffic from some malicious attacks.