Infrared image segmentation method based on 2D histogram shape modification and optimal objective function

In the methods of image thresholding segmentation, such methods based on two-dimensional （2D） histogram and optimal objective functions are important. However, when they are used for infrared image segmentation, they are weak in suppressing background noises and worse in segmenting targets with non-uniform gray level. The concept of 2D histogram shape modification is proposed, which is realized by target information prior restraint after enhancing target information using plateau histogram equalization. The formula of 2D minimum Renyi entropy is deduced for image segmentation, then the shape-modified 2D histogram is combined wfth four optimal objective functions （i.e., maximum between-class variance, maximum entropy, maximum correlation and minimum Renyi entropy） respectively for the appli- cation of infrared image segmentation. Simultaneously, F-measure is introduced to evaluate the segmentation effects objectively. The experimental results show that F-measure is an effective evaluation index for image segmentation since its value is fully consistent with the subjective evaluation, and after 2D histogram shape modification, the methods of optimal objective functions can overcome their original forms＇ deficiency and their segmentation effects are more or less improvements, where the best one is the maximum entropy method based on 2D histogram shape modification.

Variable Selection of Generalized Regression Models Based on Maximum Rank Correlation

In this paper, we investigate the variable selection problem of the generalized regression models. To estimate the regression parameter, a procedure combining the rank correlation method and the adaptive lasso technique is developed, which is proved to have oracle properties. A modified IMO （iterative marginal optimization） algorithm which directly aims to maximize the penalized rank correlation function is proposed. The effects of the estimating procedure are illustrated by simulation studies.

Oblique shock train motion based on schlieren image processing

In this paper,shock train motion in a Mach number 2.7 duct is studied experimentally,and large numbers of schlieren images are obtained by a high-speed camera.An image processing method based on Maximum Correlation Detection(MCD)is proposed to detect shock train motion from the schlieren images,based on which the key structures,e.g.,separation positions and separation shock angles on the top and bottom walls,can be analysed in detail.The oscillations of the shock train are generated by rhombus and ellipse shafts at various excitation frequencies.According to the analysis of MCD results,the distributions of the frequency components of shock train oscillation generated by the two shafts are distinctly different,in which the motion generated by the ellipse shaft is much smoother;shock train motion is mainly characterized by the oscillation of separation position while the separation shock strength is not so sensitive to downstream disturbance;there is a hysteresis loop relation between the downstream pressure and separation position.

Direct GPS P-Code Acquisition Method Based on FFT

Recently, direct acquisition of GPS P-code has received considerable attention to enhance the anti-jamming and anti-spoofing capabilities of GPS receivers. This paper describes a P-code acquisition method that uses block searches with large-scale FFT to search code phases and carrier frequency offsets in parallel. To limit memory use, especially when implemented in hardware, only the largest correlation result with its position information was preserved after searching a block of resolution cells in both the time and frequency domains. A second search was used to solve the code phase slip problem induced by the code frequency offset, Simulation results demonstrate that the probability of detection is above 0.99 for carrier-to-noise density ratios in excess of 40 dB. Hz when the predetection integration time is 0.8 ms and 6 non- coherent integrations are used in the analysis.

Ocean surface current retrieval at Hangzhou Bay from Himawari-8 sequential satellite images

Ocean surface currents play a key role in the earth’s climate.They affect virtually all processes occurring in the ocean and can also directly affect many important socio-economic activities.Himawari-8 meteorological satellite has an international advanced geostationary orbit imager sensor,AHI,with high time resolution and spatial coverage,Himawari-8 can be used to observe the subtle changes in marine environments.In this study,we used Himawari-8 data received from the Joint Receiving Station for Satellite Remote Sensing of Xiamen University to retrieve coastal currents in Hangzhou Bay.Particularly,the Maximum Correlation Coefficient(MCC)and the Generalized Hough Transform(GHT)methods were used to retrieve them respectively.The retrieved sea surface currents are analyzed and verified by the numerical model data of the Taiwan Strait current forecasting system(TFOR).The results show that(1)the Himawari-8 satellite data can be used to effectively estimate the ocean current;(2)The results of the two methods are in agreement with each other,and the error in the current measured using the GHT method is smaller in the Yangtze estuary and offshore areas,where the turbidity characteristic front is stronger.