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binary Image Steganalysis Based on Symmetrical Local Residual Patterns

Chinese Journal of Electronics 2022年第4期31卷 752-763页

作者： LUO Junwei YU Mujian YIN Xiaolin LU Wei School of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security TechnologyMinistry of Education Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-sen University

Residual computation is an effective method for gray-scale image steganalysis. For binary images, the residual computation calculated by the XOR operation is also employed in the local residual patterns(LRP) model for steganalysis. A binary image steganalytic scheme based on symmetrical local residual patterns(SLRP) is proposed. The symmetrical relationships among residual patterns are introduced that make the features more compact while reducing the dimensionality of the features set. Multi-scale windows are utilized to construct three SLRP submodels which are further merged to construct the final features set instead of a single *** with higher probability to be modified after embedding are emphasized and selected to construct the feature sets for training the support vector machine classifier. The experimental results show that the proposed steganalytic scheme is effective for detecting binary image steganography.

关键词： feature extraction symmetrical local residual patterns image coding probability Data security steganography residual computation Other topics in statistics matrix algebra Computer vision and image processing techniques pattern classification gray-scale image steganalysis local residual patterns model Image and video coding binary image steganalytic scheme support vector machines symmetrical relationships binary images binary image steganalysis Cryptography Optical, image and video signal processing binary image steganography

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Use of Sentinel-1 imagery for flood management in a reservoir-regulated river basin

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Frontiers of Earth Science 2018年第3期12卷 506-520页

作者： T. PERROU A. GAR/OUD I. PARCHARIDIS Department of Geography Harokopio University of Athens Athens Greece European Space Agency/ESRIN Frascati Rome Italy Department of Geography University Paris Diderot Paris France

Flood hazard monitoring and mapping is of great importance because it represents a significant contribution to risk management. The present study investigated the flood event that occurred downstream from the transboundary Strymon River basin, more specifically at Serres basin-a reservoir-regulated basin, in the beginning of 2015. The focus of this study was to better understand the spatio-temporal dynamic of the flood and the causes that initiated the hazard. Within the Serres basin, the Strymon transboundary river outflows to Lake Kerkini, which regulates water flow downstream for irrigation purposes and flood protection. For this research, a dataset of Sentinel-1 SAR GRD images was collected and processed covering the period of October 2014-October 2015 to investigate the water level changes in Lake Kerkini. Based on SAR images, binary water/non-water products and multitemporal RGB amplitude images were generated and interpreted. Sentinel-1 products have proved to be an effective tool on flood hazard dynamic extension mapping and estimation of water extent bodies retained by small reservoirs. In agreement with hydro-meteorological data and the high-resolution DEM, it was conceived that the flood event occurred due to the water volume flowing from upstream in the reservoir and the large amount of water draining from the tributaries into nearby sub-basins. Moreover, inefficient water management of the overwhelming water flow through the dam could further strengthen the flood event. The proposed approach, which is entirely based on open access remotely sensed data and processing tools, could be implemented in the same area for past flood events to produce archive retrospective data, as well as in other similar reservoir-regulated river basins in terms of water management and flood risk management.

关键词： flood mapping Sentinel-1 SAR binary images multitemporal image river basin

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New Algorithm for binary Connected-Component Labeling Based on Run-Length Encoding and Union-Find Sets

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Journal of Beijing Institute of Technology 2010年第1期19卷 71-75页

作者：王洪涛罗长洲王渝郭贺赵述芳 School of Automation Beijing Institute of Technology Beijing Institute of Control and Electronic Technology

Based on detailed analysis of advantages and disadvantages of the existing connected-component labeling （CCL） algorithm,a new algorithm for binary connected components labeling based on run-length encoding （RLE） and union-find sets has been put *** new algorithm uses RLE as the basic processing unit,converts the label merging of connected RLE into sets grouping in accordance with equivalence relation,and uses the union-find sets which is the realization method of sets grouping to solve the label merging of connected *** the label merging procedure has been optimized：the union operation has been modified by adding the ＂weighted rule＂ to avoid getting a degenerated-tree,and the ＂path compression＂ has been adopted when implementing the find operation,then the time complexity of label merging is O（nα（n））.The experiments show that the new algorithm can label the connected components of any shapes very quickly and exactly,save more memory,and facilitate the subsequent image analysis.

关键词： binary images connected-component labeling run-length encoding union-find sets

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