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Combination of different observation types through a multi-resolution representation of the regional gravity field using the pyramid algorithm and parameter estimation

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JOURNAL OF GEODESY 2022年第10期96卷 1-20页

作者： Liu, Qing Schmidt, Michael Sanchez, Laura Tech Univ Munchen DGFI TUM Deutsch Geodat Forschungsinst Arcisstr 21 D-80333 Munich Germany

The optimal combination of different types of gravity observations is the key to obtaining a high-resolution and high-precision regional gravity model. Current studies based on spherical radial basis functions (SRBFs) majorly consider a single-level approach for data combination. Despite the promising results reported in numerous publications, it has been suspected that the single-level model might be biased towards high-resolution measurements. Instead, a multi-resolution representation (MRR) can be applied to further take into consideration the varying spectral sensitivities of different observation techniques. In this study, we develop a new MRR scheme based on the pyramid algorithm and sequential parameter estimation. We propose strategies to solve the challenges in the practical application of the pyramid algorithm, and this study represents its first successful realization in regional gravity field modeling. The modeling results based on both simulated and real gravity data show that either the single-level approach or the MRR without pyramid algorithm is able to capture gravity information from lower resolution measurements as sufficient as our newly developed MRR algorithm. In the simulated case, the RMS error w.r.t. the validation data obtained by the MRR based on the pyramid algorithm decreases by 50% and 35%, in comparison to that of the single-level model and the MRR without pyramid algorithm, respectively. In the real case, the improvement achieved by the MRR based on the pyramid algorithm is 35% and 23% in the onshore area, and it reaches 63% and 57% in the offshore area, compared to the single-level approach and the MRR without pyramid algorithm, respectively.

关键词： Heterogeneous data combination Multi-resolution representation pyramid algorithm Regional gravity filed modeling Spherical radial basis functions

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Chemical Identification in the Specular and Off-Specular Rough-Surface Scattered Terahertz Spectra Using Wavelet Shrinkage

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IEEE ACCESS 2021年 9卷 29746-29754页

作者： Khani, Mahmoud E. Arbab, M. Hassan SUNY Stony Brook Dept Biomed Engn Stony Brook NY 11794 USA

We present the development and implementation of a novel wavelet shrinkage technique for the retrieval of obscured characteristic resonant signatures in the scattered terahertz (THz) reflectivity of molecular crystals. In this implementation, the wavelet basis functions associated with the absorption features were identified using the second-order total variation of the wavelet coefficients. Additionally, wavelet coefficients at certain scales were modified using the phase function corrections and wavelet hard thresholding. Reconstruction of the original spectra using these modified wavelet coefficients yielded the exact resonant frequencies of the chemicals, which were otherwise unrecognizable in the spectral artifacts of the rough surface scattering. We examined the robustness of this method over controlled levels of rough surface scattering, validated using the Kirchhoff approximation, in spectroscopic targets made from alpha-lactose monohydrate and 4-aminobenzoic acid (PABA), which have close spectral lines. We successfully retrieved the spectral absorption fingerprints in both specular and off-specular reflection geometries. This technique can be utilized for stand-off material characterization using the THz reflection spectroscopy in uncontrolled environments and potentially can be adopted for other broadband spectroscopic modalities.

关键词： Chemical identification maximal overlap discrete wavelet transform (MODWT) phase function effects pyramid algorithm reflection-mode spectroscopy rough surface scattering terahertz time-domain spectroscopy (THz-TDS) wavelet shrinkage off-specular scattered spectra

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Details-preserving multi-exposure image fusion based on dual-pyramid using improved exposure evaluation

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RESULTS IN OPTICS 2021年 2卷

作者： Wu, Lingfeng Hu, Junbao Yuan, Chang Shao, Zhongbao Guangdong Univ Sci & Technol Coll Mech & Elect Engn Dongguan 523083 Guangdong Peoples R China Shenzhen Univ Inst Micronano Optoelect Shenzhen 518060 Guangdong Peoples R China Beijing Inst Technol Sch Mat Beijing 100081 Peoples R China Guangzhou Coll Technol & Business Dept Elect Guangzhou 510850 Guangdong Peoples R China

Due to a limited dynamic range of widely used image recorders, it is difficult to record complete information on real scenes using a single image, and a restricted range of contrast, brightness and chromaticity can only be recorded. To mitigate this matter, a set of images of the identical scenery could be firstly captured at different exposure situations, and next be merged into an informative image via image fusion. In the paper, we present a well details-preserving image fusion technique via improved exposure evaluation and dual-pyramid model. The proposed method owning to its advantages of cost-effective, computation-stable and adaptive image processing can achieve a high dynamic range image from a set of multiple exposure sequences even for extremely complicated scenes. Experimental results demonstrated that the proposed method has richer details and better visual effects compared with the other commonly used techniques in most cases. Therefore, it could provide useful help and inspiration for image processing and enhancement field such as digital photography, remote sensing and medical imaging.

关键词： Image fusion Exposure evaluation Image quality assessment pyramid algorithm

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A novel double fine guide sensor design on space telescope 4

A novel double fine guide sensor design on space telescope

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4th Seminar on Novel Optoelectronic Detection Technology and Application

作者： Zhang Xu-xu Yin Da-yi Chinese Acad Sci Shanghai Inst Tech Phys Shanghai 200083 Peoples R China Shanghai Inst Tech Phys CAS Key Lab Infrared Syst Detect & Imaging Techno Shanghai 200083 Peoples R China Univ Chinese Acad Sci Beijing 100039 Peoples R China

ISBN: (数字)9781510619487

ISBN: (纸本)9781510619487

To get high precision attitude for space telescope, a double marginal FOV (field of view) FGS (Fine Guide Sensor) is proposed. It is composed of two large area APS CMOS sensors and both share the same lens in main light of sight. More star vectors can be get by two FGS and be used for high precision attitude determination. To improve star identification speed, the vector cross product in inter-star angles for small marginal FOV different from traditional way is elaborated and parallel processing method is applied to pyramid algorithm. The star vectors from two sensors are then used to attitude fusion with traditional QUEST algorithm. The simulation results show that the system can get high accuracy three axis attitudes and the scheme is feasibility.

关键词： fine guide sensor star identification marginal FOV pyramid algorithm attitude determination

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A Star Pattern Identification algorithm Based on Wheel Code Feature

A Star Pattern Identification Algorithm Based on Wheel Code ...

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Annual Conference of the Chinese-Society-for-Optical-Engineering (CSOE) on Applied Optics and Photonics China (AOPC) - Optical Sensing and Imaging Technology and Applications

作者： Shao Yuancheng Gao Wei Song Zongxi Wei Xin Xian Inst Opt & Precis Mech CAS Space Opt Lab Xian 710119 Shaanxi Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (数字)9781510614062

ISBN: (纸本)9781510614062;9781510614055

pyramid algorithm and grid algorithm are typical algorithms for all-sky autonomous star identification, and it has advantages of high recognition rate, and fast in running. However their recognition rate decreases rapidly when the position noise, lost stars or fake stars exist in the star image. In order to improve the performance of star sensor, a new star identification algorithm based on star pattern of wheel code is proposed. The algorithm combines the main star and its surrounding neighbor stars to form the characteristic unit, and then constructs the corresponding code feature and the wheel feature respectively. In the process of star matching, the algorithm uses the code feature of the observation star as an index to Inquire storage address of the candidate navigation star, and then calculates the similarity of wheel feature between the candidate navigation star and the observation. Simulation shows that: compared to the grid algorithm, this algorithm has higher rate of correct star recognition and better robustness. When the position error is 1 pixel and 2 lost stars exist in star image, this algorithm can reach 98.4% on identification rate, while the grid algorithm is 94.6%, and the pyramid algorithm is 83.5%;when the position error is 1 pixel and 2 fake stars exist in star image, this algorithm can reach 98.6% on identification rate, while the grid algorithm is 92.3%, and the pyramid algorithm is 87.2%.

关键词： star sensor star identification grid algorithm pyramid algorithm star pattern of wheel code

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A Novel Technique for Non-overlapping Image Mosaicing based on pyramid Method

A Novel Technique for Non-overlapping Image Mosaicing based ...

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10th Annual Conference of the IEEE-India-Council (INDICON)

作者： Pandey, Achala Pati, Umesh C. Natl Inst Technol Dept Elect & Commun Engn Rourkela 769008 India

ISBN: (纸本)9781479922741;9781479922758

Image mosaicing has been used in various arenas of image engineering. The main purpose of this research work is to develop a novel blending algorithm for mosaicing of two non-overlapping images with minimum distortion and no visible seam. In the proposed method, images are mosaiced using the pyramid technique and Savitzky-Golay filter is used for smoothing the seam between the images in the generated mosaic. Savitzky-Golay filter, is based on the least square fitting of polynomial functions of image intensities. It effectively reduces the noise and preserves the image information content resulting in a visually pleasing mosaiced image. The results and comparative analysis show the effectiveness of the proposed method.

关键词： Image blending mosaicing pyramid algorithm Savitzky-Golay filter

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A Novel Technique for Non-overlapping Image Mosaicing based on pyramid Method

A Novel Technique for Non-overlapping Image Mosaicing based ...

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Annual IEEE India Conference

作者： Achala Pandey Umesh C. Pati Dept. of Electronics and Communication Engg. National Institute of Technology Rourkela-769008 India

ISBN: (纸本)9781479922765

关键词： Image blending mosaicing pyramid algorithm Savitzky-Golay filter

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Support Vector Machine-based Image Segmentation Approach for Automatic Agriculture Vehicle

Support Vector Machine-based Image Segmentation Approach for...

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4th International Conference on Image Analysis and Signal Processing (IASP)

作者： Han, Yonghua Wang, Yaming Zhao, Yun Zhejiang Univ Sch Biosyst Engn & Food Sci Hangzhou 310003 Zhejiang Peoples R China Zhejiang Sci Tech Univ Coll Elect & Informat Hangzhou Peoples R China Zhejiang Sci Tech Univ Mech Coll Hangzhou Peoples R China

ISBN: (纸本)9781467325455;9781467325479

Support Vector Machine, a statistic procedure, is robust and has good performance when applied to farmland image segmentation. It can effectively identify the crop rows, even though they have some intersection at some points because of weeds of the leaves growth of the crops. However, the Support Vector Machine has relatively high time complexity and cannot meet the requirements of real-time processing. Based on the pyramid algorithm, we can obtain a low-resolution representation of the images being processed. Then training and testing are applied in the low-resolution images only. Through this method, the time consumption is significantly lower than the original Support Vector Machine Procedure. The objects in farmland images are large and there are only two major types of structures in them, so the examination accuracy of the proposed method is changed little. At the same time, based on spatial structure and color distribution of the farmland image, the kernel and main parameters of Support Vector Machine are selected.

关键词： guidance Support Vector Machine image segmentation pyramid algorithm

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Segmentwise Computation of 2D Forward Discrete Wavelet Transform

Segmentwise Computation of 2D Forward Discrete Wavelet Trans...

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33rd International Conference on Telecommunication and Signal Processing

作者： Prusa, Zdenek Rajmic, Pavel Maly, Jan Brno Univ Technol Fac Elect Engn & Commun Dept Telecommun Brno 61200 Czech Republic

ISBN: (纸本)9789638898104

In this paper we present a new algorithm for segmentwise computation of 2D forward discrete-time wavelet transform. The idea of the algorithm is that the 2D discrete signal (image) is divided into rectangular segments and the computation of the wavelet transform coefficients can be performed on each of the segments independently. The algorithm introduces substantial advantage in that the transform can be performed on segments in parallel with the cost of a slight redundancy (several coefficients are computed more than once). The size of the segments is arbitrary in both the vertical and the horizontal directions, so there is place for performance tuning. Another usage of the algorithm is in the processing of large-scale images. Such images are not expected to fit into operating memory of the device, so the natural approach is to load one segment at a time and process it. We also present our implementation of the algorithm in parallel 2D forward DTWT using C++ and Intel Threading Building Blocks library.

关键词： digital image processing pyramid algorithm parallelization discrete-time wavelet transform segmentation Intel Threading Building Blocks

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Improvement Mean Shift-based Image Segmentation Approach for Automatic Agriculture Vehicle

Improvement Mean Shift-based Image Segmentation Approach for...

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Conference on International Conference on Image Processing and Pattern Recognition in Industrial Engineering

作者： Han, Yong-hua Wang, Ya-ming Zhao, Yun Zhejiang Univ Sch Biosyst Engn & Food Sci Hangzhou 310029 Zhejiang Peoples R China Zhejiang Sci Tech Univ Coll Elect & Informat Hangzhou 310018 Peoples R China

ISBN: (纸本)9780819483294

Mean Shift algorithm, a statistic iterative procedure, is robust when applied to farmland image segmentation. It can effectively overcome the influence of shadow, weeds or illumination changes, etc. However, the Mean Shift procedure has relatively high time complexity and can not meet the requirements of real-time processing. Based on pyramid algorithm, we can obtain a low resolution representation of the images being processed. Then, run Mean shift algorithm on a set of seed points that selected in the low resolution image. Through this method, the time consumption is significantly lower than the original Mean Shift Procedure. The objects in farmland images are large and there are only two major types of structure in it, so the examination accuracy of proposed method is changed little. At the same time based on spatial structure and color distribution of farmland image, Mean Shift Kernel radius in the spatial and range domain is selected. In addition, according to different seasons, crops show different colors. In this case, the equations which convert color image into a grayscale image are discussed.

关键词： Mean Shift image segmentation pyramid algorithm seed points auto-navigation

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