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	Comprehensive evaluation of precipitation datasets over Iran 期刊论文 OAI收割 JOURNAL OF HYDROLOGY, 2021, 卷号: 603, 页码: 23 作者: Saemian, Peyman; Hosseini-Moghari, Seyed-Mohammad; Fatehi, Iman; Shoarinezhad, Vahid; Modiri, Ehsan \| 收藏 \| 浏览/下载：30/0 \| 提交时间：2022/09/21 Gauge-based products Reanalysis products Satellite observations Statistical evaluation Point-to-pixel approach Pixel-to-pixel approach
	Comprehensive evaluation of precipitation datasets over Iran 期刊论文 OAI收割 JOURNAL OF HYDROLOGY, 2021, 卷号: 603, 页码: 23 作者: Saemian, Peyman; Hosseini-Moghari, Seyed-Mohammad; Fatehi, Iman; Shoarinezhad, Vahid; Modiri, Ehsan \| 收藏 \| 浏览/下载：16/0 \| 提交时间：2022/09/21 Gauge-based products Reanalysis products Satellite observations Statistical evaluation Point-to-pixel approach Pixel-to-pixel approach
	Image matching using a bat algorithm with mutation (EI CONFERENCE) 会议论文 OAI收割 2012 International Conference on Mechatronic Systems and Automation Systems, MSAS 2012, July 21, 2012 - July 21, 2012, Wuhan, China 作者: Zhang J.; Wang G.; Zhang J.; Zhang J. 收藏 \| 浏览/下载：38/0 \| 提交时间：2013/03/25 Due to shortcoming of traditional image matching for computing the fitness for every pixel in the searching space a new bat algorithm with mutation (BAM) is proposed to solve image matching problem and a modification is applied to mutate between bats during the process of the new solutions updating. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for this improved meta-heuristic approach BAM is also presented. To prove the performance of this proposed meta-heuristic method BAM is compared with BA and other population-based optimization methods DE and SGA. The experiment shows that the proposed approach is more effective and feasible in image matching than the other model. (2012) Trans Tech Publications Switzerland.
	Multiwavelet based multispectral image fusion for corona detection (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wang X.; Yang H.-J.; Sui Y.-X.; Yan F.; Yan F. 收藏 \| 浏览/下载：29/0 \| 提交时间：2013/03/25 Image fusion refers to the integration of complementary information provided by various sensors such that the new images are more useful for human or machine perception. Multiwavelet transform has simultaneous orthogonality symmetry compact support and vanishing moment which are not possible with scalar wavelet transform. Multiwavelet analysis can offer more precise image analysis than wavelet multiresolution analysis. In this paper a new image fusion algorithm based on discrete multiwavelet transform (DMWT) to fuse the dual-spectral images generated from the corona detection system is presented. The dual-spectrum detection system is used to detect the corona and indicate its exact location. The system combines a solar-blind UV ICCD with a visible camera where the UV image is useful for detecting UV emission from corona and the visible image shows the position of the corona. The developed fusion algorithm is proposed considering the feature of the UV and visible images adequately. The source images are performed at the pixel level. First a decomposition step is taken with the DMWT. After the decomposition step a pyramid for each source image in each level can be obtained. Then an optimized coefficient fusion rule consisting of activity level measurement coefficient combining and consistency verification is used to acquire the fused coefficients. This process reduces the impulse noise of UV image. Finally a new fused image is obtained by reconstructing the fused coefficients using inverse DMWT. This image fusion algorithm has been applied to process the multispectral UV/visible images. Experimental results show that the proposed method outperforms the discrete wavelet transform based approach.
	Measuring the system gain of the TDI CCD remote sensing camera (EI CONFERENCE) 会议论文 OAI收割 Advanced Materials and Devices for Sensing and Imaging II, November 8, 2004 - November 10, 2004, Beijing, China Ya-xia L.; Hai-ming B.; Jie L.; Jin R.; Zhi-hang H. 收藏 \| 浏览/下载：62/0 \| 提交时间：2013/03/25 The gain of a TDI CCD camera is the conversion between the number of electrons recorded by the TDI CCD and the number of digital units (counts) contained in the CCD image"[1]. TDI CCD camera has been a main technical approach for meeting the requirements of high-resolution and lightweight of remote sensing equipment. It is useful to know this conversion for evaluating the performance of the TDI CCD camera. In general a lower gain is better. However the resulting slope is the gain of the TDI CCD. We did the experiments using the Integration Sphere in order to get a flat field effects. We calculated the gain of the four IT-EI-2048 TDI CCD. The results and figures of the four TDI CCD are given. this is only true as long as the total well depth (number of electrons that a pixel can hold) of the pixels can be represented. High gains result in higher digitization noise. System gains are designed to be a compromise between the extremes of high digitization noise and loss of well depth. In this paper the mathematical theory is given behind the gain calculation on a TDI CCD camera and shows how the mathematics suggests ways to measure the gain accurately according to the Axiom Tech. The gains were computed using the mean-variance method also known as the method of photon transfer curves. This method uses the effect of quantization on the variance in the measured counts over a uniformly illuminated patch of the detector. This derivation uses the concepts of signal and noise. A linear fit is done of variance vs. mean
	Research on the nonuniformity correction of linear TDI CCD remote camera (EI CONFERENCE) 会议论文 OAI收割 Advanced Materials and Devices for Sensing and Imaging II, November 8, 2004 - November 10, 2004, Beijing, China Ya-xia L.; Zhi-hang H. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 Many applications such as industrial inspection and overhead reconnaissance benefit from line scanning architectures where time delay integration (TDI) significantly improves sensitivity[5]. Images with linear response have become the backbone of the imaging industry. But each pixel of the TDI CCD has unique light sensitivity characteristics. Because these characteristics and the lens of the optical system affect camera's linearization and its performance they must be removed through calibration. The process by which a CCD image is calibrated is known as nonuniformity correction. This paper discusses several methods of nonuniformity correction[2]. The first is one-point correction technique which requires only one calibration point. This approach is to shift each curve toward the nominal curve by subtracting the offset from or adding the offset to the average. The second is two-point correction technique which requires two calibration points. Each point is rotated and aligned so that all the detectors have the same response under the same radiance. The third is multipoint correction. It is recommended that more calibration points be implemented at appropriate regions of the response curve. Depend on the linear photoelectric response of the TDI CCD we use two-point calibration and the standard deviations for the images are given before and after the correction.