In order to enhance the image information from multi-sensor and to improve the abilities of the information analysis and the feature extraction, this letter proposed a new fusion approach in pixel level by means of th...In order to enhance the image information from multi-sensor and to improve the abilities of the information analysis and the feature extraction, this letter proposed a new fusion approach in pixel level by means of the Wavelet Packet Transform (WPT). The WPT is able to decompose an image into low frequency band and high frequency band in higher scale. It offers a more precise method for image analysis than Wavelet Transform (WT). Firstly, the proposed approach employs HIS (Hue, Intensity, Saturation) transform to obtain the intensity component of CBERS (China-Brazil Earth Resource Satellite) multi-spectral image. Then WPT transform is employed to decompose the intensity component and SPOT (Systeme Pour I'Observation de la Therre ) image into low frequency band and high frequency band in three levels. Next, two high frequency coefficients and low frequency coefficients of the images are combined by linear weighting strategies. Finally, the fused image is obtained with inverse WPT and inverse HIS. The results show the new approach can fuse details of input image successfully, and thereby can obtain a more satisfactory result than that of HM (Histogram Matched)-based fusion algorithm and WT-based fusion approach.展开更多
As a major global exchange, the Stock Exchange of Hong Kong （SEHK） only requires semi-annual reporting whereas other major exchanges including the ones in Chinese mainland require quarterly reporting. We argue again...As a major global exchange, the Stock Exchange of Hong Kong （SEHK） only requires semi-annual reporting whereas other major exchanges including the ones in Chinese mainland require quarterly reporting. We argue against the traditional view that higher reporting frequency is necessarily more beneficial. The decision on reporting frequency depends on how the information is being processed by the recipient traders and the results are not obvious. Using a sample of Chinese companies dual- listed in both China A share market and SEHK （AH shares） as the experimental group and mainland＇s companies listed on SEHK （H shares） only as the control group, we apply the difference-in-difference （DID） method to investigate the impacts of reporting frequency on stock information quality. The results suggest that after China A share market require quarterly financial reporting for all listed companies in 2002, the information asymmetry of the H tranche of AH stocks increases. Different from prior studies, the results suggest a negative association between stock information quality and financial reporting frequency. We argue that the increased information asymmetry in the H tranche is caused by the noise spilled over from the A tranche. We conduct multivariable GARCH tests and find evidence supporting this conjecture.展开更多
Digital data of precursors is noted for its high accuracy. Therefore, it is important to extract the high frequency information from the low ones in the digital data of precursors and to discriminate between the trend...Digital data of precursors is noted for its high accuracy. Therefore, it is important to extract the high frequency information from the low ones in the digital data of precursors and to discriminate between the trend anomalies and the short-term anomalies. This paper presents a method to separate the high frequency information from the low ones by using the wavelet transform to analyze the digital data of precursors, and illustrates with examples the train of thoughts of discriminating the short-term anomalies from trend anomalies by using the wavelet transform, thus provide a new effective approach for extracting the short-term and trend anomalies from the digital data of precursors.展开更多
文摘In order to enhance the image information from multi-sensor and to improve the abilities of the information analysis and the feature extraction, this letter proposed a new fusion approach in pixel level by means of the Wavelet Packet Transform (WPT). The WPT is able to decompose an image into low frequency band and high frequency band in higher scale. It offers a more precise method for image analysis than Wavelet Transform (WT). Firstly, the proposed approach employs HIS (Hue, Intensity, Saturation) transform to obtain the intensity component of CBERS (China-Brazil Earth Resource Satellite) multi-spectral image. Then WPT transform is employed to decompose the intensity component and SPOT (Systeme Pour I'Observation de la Therre ) image into low frequency band and high frequency band in three levels. Next, two high frequency coefficients and low frequency coefficients of the images are combined by linear weighting strategies. Finally, the fused image is obtained with inverse WPT and inverse HIS. The results show the new approach can fuse details of input image successfully, and thereby can obtain a more satisfactory result than that of HM (Histogram Matched)-based fusion algorithm and WT-based fusion approach.
文摘As a major global exchange, the Stock Exchange of Hong Kong （SEHK） only requires semi-annual reporting whereas other major exchanges including the ones in Chinese mainland require quarterly reporting. We argue against the traditional view that higher reporting frequency is necessarily more beneficial. The decision on reporting frequency depends on how the information is being processed by the recipient traders and the results are not obvious. Using a sample of Chinese companies dual- listed in both China A share market and SEHK （AH shares） as the experimental group and mainland＇s companies listed on SEHK （H shares） only as the control group, we apply the difference-in-difference （DID） method to investigate the impacts of reporting frequency on stock information quality. The results suggest that after China A share market require quarterly financial reporting for all listed companies in 2002, the information asymmetry of the H tranche of AH stocks increases. Different from prior studies, the results suggest a negative association between stock information quality and financial reporting frequency. We argue that the increased information asymmetry in the H tranche is caused by the noise spilled over from the A tranche. We conduct multivariable GARCH tests and find evidence supporting this conjecture.
文摘Digital data of precursors is noted for its high accuracy. Therefore, it is important to extract the high frequency information from the low ones in the digital data of precursors and to discriminate between the trend anomalies and the short-term anomalies. This paper presents a method to separate the high frequency information from the low ones by using the wavelet transform to analyze the digital data of precursors, and illustrates with examples the train of thoughts of discriminating the short-term anomalies from trend anomalies by using the wavelet transform, thus provide a new effective approach for extracting the short-term and trend anomalies from the digital data of precursors.
