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Ablock-based secure and robustwatermarking scheme for color images based onmulti-resolution decomposition and de-correlation Research Articles

Muhammad IMRAN, Bruce A. HARVEY, Muhammad ATIF, Adnan Ali MEMON

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 7,   Pages 946-963 doi: 10.1631/FITEE.1700667

Abstract:

This paper presents a block-based secure and robust watermarking technique for color images based on multi-resolution decomposition and de-correlation. The principal objective of the presented scheme is to simultaneously meet all the four requirements (robustness, security, imperceptibility, and capacity) of a good watermarking scheme. The contribution of this study is to basically achieve the four contradictory requirements that a good watermarking scheme must meet. To do so, different approaches are combined in a way that the four requirements are achieved. For instance, to obtain imperceptibility, the three color channels (red, green, and blue) are de-correlated using principal component analysis, and the first principal component (de-correlated red channel) is chosen for watermark embedding. Afterwards, to achieve robustness, the de-correlated channel is decomposed using a discrete wavelet transform (DWT), and the approximate band (the other three bands are kept intact to preserve the edge information) is further decomposed into distinct blocks. The random blocks are chosen based on a random generated key. The random selected blocks are further broken down into singular values and vectors. Based on the mutual dependency on singular values and vectors’ matrices, the values are modified depending on the watermarking bits, and their locations are saved and used as another key, required when the watermark is to be extracted. Consequently, two-level authentication levels ensure the security, and using both singular values and vectors increases the capacity of the presented scheme. Moreover, the involvement of both left and right singular vectors along with singular values in the watermarking embedding process strengthens the robustness of the proposed scheme. Finally, to compare the presented scheme with the state-of-the-art schemes in terms of imperceptibility (peak signal-to-noise ratio and structural similarity index), security (with numerous fake keys), robustness (normalized correlation and bit error rate), and capacity, the Gonzalez and Kodak datasets are used. The comparison shows significant improvement of the proposed scheme over existing schemes.

Keywords： Copyright protection     Data hiding     Multi-resolution decomposition     De-correlation     Security    

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Super Resolution Perception for Improving Data Completeness in Smart Grid State Estimation Article

Gaoqi Liang, Guolong Liu, Junhua Zhao, Yanli Liu, Jinjin Gu, Guangzhong Sun, Zhaoyang Dong

Engineering 2020, Volume 6, Issue 7,   Pages 789-800 doi: 10.1016/j.eng.2020.06.006

Abstract:

The smart grid is an evolving critical infrastructure, which combines renewable energy and the most advanced information and communication technologies to provide more economic and secure power supply services. To cope with the intermittency of ever-increasing renewable energy and ensure the security of the smart grid, state estimation, which serves as a basic tool for understanding the true states of a smart grid, should be performed with high frequency. More complete system state data are needed to support high-frequency state estimation. The data completeness problem for smart grid state estimation is therefore studied in this paper. The problem of improving data completeness by recovering high-frequency data from low-frequency data is formulated as a super resolution perception (SRP) problem in this paper. A novel machine-learning-based SRP approach is thereafter proposed. The proposed method, namely the Super Resolution Perception Net for State Estimation (SRPNSE), consists of three steps: feature extraction, information completion, and data reconstruction. Case studies have demonstrated the effectiveness and value of the proposed SRPNSE approach in recovering high-frequency data from low-frequency data for the state estimation.

Keywords： State estimation     Low-frequency data     High-frequency data     Super resolution perception     Data completeness    

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MPIN: a macro-pixel integration network for light field super-resolution Research Articles

Xinya Wang, Jiayi Ma, Wenjing Gao, Junjun Jiang,wangxinya@whu.edu.cn,jyma2010@gmail.com,wenjinggao@whu.edu.cn,junjun0595@163.com

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 10,   Pages 1299-1310 doi: 10.1631/FITEE.2000566

Abstract: Most existing (LF) (SR) methods either fail to fully use angular information or have an unbalanced performance distribution because they use parts of views. To address these issues, we propose a novel integration network based on for the LF SR task, named MPIN. Restoring the entire LF image simultaneously, we couple the spatial and angular information by rearranging the four-dimensional LF image into a two-dimensional macro-pixel image. Then, two special convolutions are deployed to extract spatial and angular information, separately. To fully exploit spatial-angular correlations, the integration resblock is designed to merge the two kinds of information for mutual guidance, allowing our method to be angular-coherent. Under the , an angular shuffle layer is tailored to improve the spatial resolution of the macro-pixel image, which can effectively avoid aliasing. Extensive experiments on both synthetic and real-world LF datasets demonstrate that our method can achieve better performance than the state-of-the-art methods qualitatively and quantitatively. Moreover, the proposed method has an advantage in preserving the inherent epipolar structures of LF images with a balanced distribution of performance.

Keywords： 光场；超分辨率；宏像素表示    

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The research of inversion algorithm of significant wave height with high resolution based HY-2 waveform data

Wang Guizhong,Zhang Jie,Miao Hongli,Li Guoqiang,Wang Xin

Strategic Study of CAE 2014, Volume 16, Issue 6,   Pages 60-64

Abstract: Comparing the SWH derived from 1 s waveform, the SWH derived by this method could be increased by about

Keywords： HY-2     significant wave height     inversion algorithm     high resolution    

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Perspectives on cross-domain visual analysis of cyber-physical-social big data Perspective

Wei Chen, Tianye Zhang, Haiyang Zhu, Xumeng Wang, Yunhai Wang,cloudseawang@gmail.com

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 12,   Pages 1551-1684 doi: 10.1631/FITEE.2100553

Abstract: The domain of cyber-physical-social (CPS) big data is generally defined as the set consisting of all the elements in its defined domain, including domains of data, objects, tasks, application scenarios, and subjects. Visual analytics is an emerging human-in-the-loop big data analytics paradigm that can exploit human perception to enhance human cognitive efficiency. In this paper, we explore the perspectives on cross-domain visual analysis of CPS big data. We also highlight new challenges brought by the cross-domain nature of CPS big data—data, subject, and task domains—and propose a novel visual analytics model and a suite of approaches to address these challenges.

Keywords： 可视分析；三元空间；大数据；跨域    

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An investigation of local high spatial resolution adaptive PET system

Liu Jingjing,Xie Qingguo

Strategic Study of CAE 2011, Volume 13, Issue 10,   Pages 105-112

Abstract:

A critical challenge in positron emission tomography (PET) is to develop affordable systems having high spatial resolution. We imagine a PET system, for imaging a region of interest (ROI) with ultra high performances and other regions with normal performances by use of inhomogeneous performances PET detectors. We propose such a prototype, consisting of a few ultra high intrinsic spatial resolution PET detectors and quite a few normal ones. In this paper, we investigate the effect of the location and the number of high resolution detectors. The high resolution detectors are grouped in a continuous partial ring. The initial results show that such a prototype is capable to bring the advantages of significantly improving the spatial resolution in a ROI. For a specified area, the improvement is influenced by the location and fraction of high resolution detectors in a ring. The encouraging results also indicate the possibilities to regulate detectors to achieve high spatial resolution according to the application, which is possibly formulated.

Keywords： positron emission tomography     adaptive PET system     region of interest     local spatial resolution     inhomogeneous performance PET detector    

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High Spatial Resolution Ozone Profiles Retrieved from the First Chinese Ultraviolet–Visible Hyperspectral Satellite Instrument Article

Fei Zhao, Cheng Liu, Qihou Hu, Congzi Xia, Chengxin Zhang, Wenjing Su

Engineering 2024, Volume 32, Issue 1,   Pages 107-116 doi: 10.1016/j.eng.2023.02.020

Abstract:

Understanding the vertical distribution of ozone is crucial when assessing both its horizontal and vertical transport, as well as when analyzing the physical and chemical properties of the atmosphere. One of the most effective ways to obtain high spatial resolution ozone profiles is through satellite observations. The Environmental Trace Gases Monitoring Instrument (EMI) deployed on the Gaofen-5 satellite is the first Chinese ultraviolet-visible hyperspectral spectrometer. However, retrieving ozone profiles using backscattered radiance values measured by the EMI is challenging due to unavailable measurement errors and a low signal-to-noise ratio. The algorithm developed for the Tropospheric Monitoring Instrument did not allow us to retrieve 87% of the EMI pixels. Therefore, we developed an algorithm specific to the characteristics of the EMI. The fitting residuals are smaller than 0.3% in most regions. The retrieved ozone profiles were in good agreement with ozonesonde data, with maximum mean biases of 20% at five latitude bands. By applying EMI averaging kernels to the ozonesonde profiles, the integrated stratospheric column ozone and tropospheric column ozone also showed excellent agreement with ozonesonde data. The lower layers (0–7.5 km) of the EMI ozone profiles reflected the seasonal variation in surface ozone derived from the China National Environmental Monitoring Center (CNEMC). However, the upper layers (9.7–16.7 km) of the ozone profiles show different trends, with the ozone peak occurring at an altitude of 9.7–16.7 km in March. A stratospheric intrusion event in central China from August 11 to 15, 2019, is captured using the EMI ozone profiles, potential vorticity data, and relative humidity data. The increase in the CNEMC ozone concentration showed that downward transport enhanced surface ozone pollution.

Keywords： Ozone profiles     EMI     Soft calibration     Floor noise correction     Stratospheric ozone intrusion    

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Display Engineers Pack the Pixels

Mitch Leslie

Engineering 2021, Volume 7, Issue 7,   Pages 897-898 doi: 10.1016/j.eng.2021.06.002

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Remote Sensing and Precision Agriculture Technologies for Crop Disease Detection and Management with a Practical Application Example Review

Chenghai Yang

Engineering 2020, Volume 6, Issue 5,   Pages 528-532 doi: 10.1016/j.eng.2019.10.015

Abstract:

Remote sensing technology has long been used to detect and map crop diseases. Airborne and satellite imagery acquired during growing seasons can be used not only for early detection and within-season management of some crop diseases, but also for the control of recurring diseases in future seasons. With variable rate technology in precision agriculture, site-specific fungicide application can be made to infested areas if the disease is stable, although traditional uniform application is more appropriate for diseases that can spread rapidly across the field. This article provides a brief overview of remote sensing and precision agriculture technologies that have been used for crop disease detection and management. Specifically, the article illustrates how airborne and satellite imagery and variable rate technology have been used for detecting and mapping cotton root rot, a destructive soilborne fungal disease, in cotton fields and how site-specific fungicide application has been implemented using prescription maps derived from the imagery for effective control of the disease. The overview and methodologies presented in this article should provide researchers, extension personnel, growers, crop consultants, and farm equipment and chemical dealers with practical guidelines for remote sensing detection and effective management of some crop diseases.

Keywords： Crop disease     Airborne imagery     High-resolution satellite imagery     Cotton root rot Prescription map     Variable rate application    

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Study on channcl resolution matching algorithm for HY-2 satellite

Huang Lei,Zhou Wu,Li Yanmin

Strategic Study of CAE 2014, Volume 16, Issue 6,   Pages 65-69

Abstract:

Accuracy Satellite Scanning Microwave Radiometer ocean parameters retrieval need brightness temperature of multiple channel from same area and identical resolution. Due to the limitation of spaceborne radiometer antenna design and feedhorn arrangement, each channel has different resolution and observation position, this will increase the ocean parameter retrieval error. Based on the HY-2 Scanning microwave radiometer antenna pattern and imaging geometry, we simulate the ground footprint form different channel, use Backu-Gilbert(BG) algorithm produce a single composite sample at a particular location and with a particular spatial weighting pattern from combination of the adjacent measurements, the low frequency 6.6GHz is set as the reference channel. The result showed that the matching with resolution decreasing could simulate the real instrument observation without introducing noise.

Keywords： scanning microwave radiometer     HY-2     resolution matching     Backus-Gilbert algorithm    

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The Research of Discovery Feature Sub-space Model (DFSSM) Based on Complex Type Data

Yang Bingru,Tang Qing

Strategic Study of CAE 2003, Volume 5, Issue 1,   Pages 56-61

Abstract:

This paper discusses the macroscopic and important problem in the field of KDD. First, it is very difficult to describe the complex type data by general knowledge representation method. So the authors use pattern, which is defined as the vector in Hilbert Space, to represent the characteristic of complex type data. It also can be used to describe the rule of knowledge discovery. Second, the general structure model is constructed based on complex type data—DFSSM (discovery feature sub-space model ) following by the research on inner mechanism of knowledge discovery system. At last, the authors prove the practicability and validity of this general structure model i. e. DFSSM which can guide the knowledge discovery of textual data and image data (meteorological echogram data). It will beapplied in other complex type data in future.

Keywords： complex type data     data mining     text mining    

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Explainable data transformation recommendation for automatic visualization Research Article

Ziliang WU, Wei CHEN, Yuxin MA, Tong XU, Fan YAN, Lei LV, Zhonghao QIAN, Jiazhi XIA,wzlzju@zju.edu.cn,chenvis@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 7,   Pages 1007-1027 doi: 10.1631/FITEE.2200409

Abstract: generates meaningful visualizations to support data analysis and pattern finding for novice or casual users who are not familiar with visualization design. Current approaches adopt mainly aggregation and filtering to extract patterns from the original data. However, these limited s fail to capture complex patterns such as clusters and correlations. Although recent advances in feature engineering provide the potential for more kinds of automatic s, the auto-generated transformations lack concerning how patterns are connected with the original features. To tackle these challenges, we propose a novel explainable recommendation approach for extended kinds of s in . We summarize the space of feasible s and measures on of transformation operations with a literature review and a pilot study, respectively. A recommendation algorithm is designed to compute optimal transformations, which can reveal specified types of patterns and maintain . We demonstrate the effectiveness of our approach through two cases and a user study.

Keywords： Data transformation     Data transformation recommendation     Automatic visualization     Explainability    

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Optical Microscopy Advances Reach Sub-Nanometer Resolution

Chris Palmer

Engineering 2023, Volume 31, Issue 12,   Pages 11-14 doi: 10.1016/j.eng.2023.11.002

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RCDS: a right-confirmable data-sharing model based on symbol mapping coding and blockchain Research Article

Liang WANG, Shunjiu HUANG, Lina ZUO, Jun LI, Wenyuan LIU,wangl@hbu.edu.cn,sjhuang1120@stumail.hbu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 8,   Pages 1194-1213 doi: 10.1631/FITEE.2200659

Abstract: The problem of is a long-term bottleneck in . Existing methods for confirming data rights lack credibility owing to poor supervision, and work only with specific data types because of their technical limitations. The emergence of is followed by some new data-sharing models that may provide improved data security. However, few of these models perform well enough in confirming data rights because the data access could not be fully under the control of the facility. In view of this, we propose a right-confirmable data-sharing model named RCDS that features (SMC) and . With SMC, each party encodes its digital identity into the byte sequence of the shared data by generating a unique symbol mapping table, whereby declaration of data rights can be content-independent for any type and any volume of data. With , all data-sharing participants jointly supervise the delivery and the access to shared data, so that granting of data rights can be openly verified. The evaluation results show that RCDS is effective and practical in data-sharing applications that are conscientious about .

Keywords： Data right confirmation     Symbol mapping coding     Blockchain     Data sharing     Traitor tracing     Access control    

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Title Author Date Type Operation

The Impact of Cropland Spatial Pattern Change on Grain Production in China

Li Yuanyuan, Tan Minghong, Zhang Hongqi

Journal Article

Ablock-based secure and robustwatermarking scheme for color images based onmulti-resolution decomposition and de-correlation

Muhammad IMRAN, Bruce A. HARVEY, Muhammad ATIF, Adnan Ali MEMON

Journal Article

Super Resolution Perception for Improving Data Completeness in Smart Grid State Estimation

Gaoqi Liang, Guolong Liu, Junhua Zhao, Yanli Liu, Jinjin Gu, Guangzhong Sun, Zhaoyang Dong

Journal Article

MPIN: a macro-pixel integration network for light field super-resolution

Xinya Wang, Jiayi Ma, Wenjing Gao, Junjun Jiang,wangxinya@whu.edu.cn,jyma2010@gmail.com,wenjinggao@whu.edu.cn,junjun0595@163.com

Journal Article

The research of inversion algorithm of significant wave height with high resolution based HY-2 waveform data

Wang Guizhong,Zhang Jie,Miao Hongli,Li Guoqiang,Wang Xin

Journal Article

Perspectives on cross-domain visual analysis of cyber-physical-social big data

Wei Chen, Tianye Zhang, Haiyang Zhu, Xumeng Wang, Yunhai Wang,cloudseawang@gmail.com

Journal Article

An investigation of local high spatial resolution adaptive PET system

Liu Jingjing,Xie Qingguo

Journal Article

High Spatial Resolution Ozone Profiles Retrieved from the First Chinese Ultraviolet–Visible Hyperspectral Satellite Instrument

Fei Zhao, Cheng Liu, Qihou Hu, Congzi Xia, Chengxin Zhang, Wenjing Su

Journal Article

Display Engineers Pack the Pixels

Mitch Leslie

Journal Article

Remote Sensing and Precision Agriculture Technologies for Crop Disease Detection and Management with a Practical Application Example

Chenghai Yang

Journal Article

Study on channcl resolution matching algorithm for HY-2 satellite

Huang Lei,Zhou Wu,Li Yanmin

Journal Article

The Research of Discovery Feature Sub-space Model (DFSSM) Based on Complex Type Data

Yang Bingru,Tang Qing

Journal Article

Explainable data transformation recommendation for automatic visualization

Ziliang WU, Wei CHEN, Yuxin MA, Tong XU, Fan YAN, Lei LV, Zhonghao QIAN, Jiazhi XIA,wzlzju@zju.edu.cn,chenvis@zju.edu.cn

Journal Article

Optical Microscopy Advances Reach Sub-Nanometer Resolution

Chris Palmer

Journal Article

RCDS: a right-confirmable data-sharing model based on symbol mapping coding and blockchain

Liang WANG, Shunjiu HUANG, Lina ZUO, Jun LI, Wenyuan LIU,wangl@hbu.edu.cn,sjhuang1120@stumail.hbu.edu.cn

Journal Article