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Curvelet Approach for Deep-sea Sonar Image Denoising, Contrast Enhancement and Fusion
Lu, Huimin,Yamawaki, Akira,Serikawa, Seiichi The Korean Institute of Electrical Engineers 2013 The Journal of International Council on Electrical Vol.3 No.3
Side-scan sonar acquires high quality imagery of the seafloor with very high spatial resolution but poor locational accuracy. However, multi-beam sonar obtains high precision position and underwater depth in seafloor points. In order to fully utilize all information of these two types of sonars, it is necessary to fuse the two kinds of sonar data. This paper gives curvelet transform for enhancing the signals or details in different scales separately. It also proposes a new intensity sonar image fusion method, which is based on curvelet transform. Considering the sonar image forming principle, for the low frequency curvelet coefficients, we use the maximum local energy method to calculate the energy of two sonar images. For the high frequency curvelet coefficients, we take absolute maximum method as a measurement. The main attribute of this paper is: Firstly, the multi-resolution analysis method is well adapted the cured-singularities and point-singularities. It is useful for sonar intensity image enhancement. Secondly, maximum local energy is well performing the intensity sonar images, which can achieve perfect fusion result. The experimental results show that the method can be used in the flat seafloor or the isotropic seabed. Compared with wavelet transform method, this method can get better performance.
A method for extraction of arbitrary figure using one-dimensional histogram
Shota Nakashima,Makoto Miyauchi,Seiichi Serikawa 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
An extraction of a specific figure in image has basic problems in intelligent image sensing. The generalized Hough transform (GHT) is the representative method to extract arbitrary figures which are rotated and enlarged or reduced. Many the improvement models were also proposed. However, for extraction of arbitrary figures, it takes much processing time and needs much memory space. In addition, it is impossible to apply the GHT to figures including branches. For an improvement of the problems, a new method to extract arbitrary figure using one-dimensional histogram is proposed in this study. The method utilizes the Polytope method which is one of minimization algorithms. For the extraction of figures, one-dimensional histogram is used. The histogram has two characteristics. (1) The distribution of histogram changes if the parameters representing figure changes. (2) The best parameters are gotten, if the value of most frequency of histogram becomes maximum. Therefore, by using the Polytope method, the best parameters are searched so that the maximum value of most frequency can be maximum. In comparison with conventional method, it is understood that memory space is very small, processing time is very short and figures including branches can be extracted. In addition, this method is effective for an extraction of arbitrary figure with different aspect ratio.
Adaptive Beamforming Algorithms for Smart Antenna Systems
Shahera HOSSAIN,Mohammad Tariqul ISLAM,Seiichi SERIKAWA 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
Wireless communication is one of the most rapidly growing industries. The high demand for wireless communication services had led to an increase in system capacity. Then most elementary solution would be to increase bandwidth; however, this becomes ever more challenging as the electromagnetic spectrum is becoming increasingly congested. The ever-increasing demand for increased capacity in wireless communications services has led to developments of new technologies that exploit space selectivity. This is done through smart-antenna arrays and the associated adaptive beamforming algorithms. Smart-antenna systems provide opportunities for higher system capacity and improved quality of service among other things In this paper, two non-blind algorithms: Least Mean Square (LMS) and Normalized Least Mean Square (NLMS) algorithms were compared for a robust smart antenna system. It has been found that NLMS performs better in many respects than LMS and so we propose NLMS to be used by mobile companies when they will use smart antenna. Our findings are explained in details in the result and analysis section with graphs. Our comparison and findings were simulated using MATLAB.