Compressed data separation via dual frames based split-analysis with Weibull matrices

In this paper, we consider data separation problem, where the original signal is composed of two distinct subcomponents, via dual frames based Split-analysis approach. We show that the two distinct subcomponents, which are sparse in two diff erent general frames respectively, can be exactly recovered with high probability, when the measurement matrix is a Weibull random matrix （not Gaussian） and the two frames satisfy a mutual coherence property. Our result may be significant for analysing Split-analysis model for data separation.

Water storage changes in North America retrieved from GRACE gravity and GPS data

As global warming continues,the monitoring of changes in terrestrial water storage becomes increasingly important since it plays a critical role in understanding global change and water resource management.In North America as elsewhere in the world,changes in water resources strongly impact agriculture and animal husbandry.From a combination of Gravity Recovery and Climate Experiment（GRACE） gravity and Global Positioning System（GPS） data,it is recently found that water storage from August,2002 to March,2011 recovered after the extreme Canadian Prairies drought between 1999 and 2005.In this paper,we use GRACE monthly gravity data of Release 5 to track the water storage change from August,2002 to June,2014.In Canadian Prairies and the Great Lakes areas,the total water storage is found to have increased during the last decade by a rate of 73.8 ± 14.5 Gt/a,which is larger than that found in the previous study due to the longer time span of GRACE observations used and the reduction of the leakage error.We also find a long term decrease of water storage at a rate of-12.0 ± 4.2 Gt/a in Ungava Peninsula,possibly due to permafrost degradation and less snow accumulation during the winter in the region.In addition,the effect of total mass gain in the surveyed area,on present-day sea level,amounts to-0.18 mm/a,and thus should be taken into account in studies of global sea level change.

Adaptive Particle Swarm Optimization Data Hiding for High Security Secret Image Sharing

The main aim of this work is to improve the security of data hiding forsecret image sharing. The privacy and security of digital information have becomea primary concern nowadays due to the enormous usage of digital technology.The security and the privacy of users’ images are ensured through reversible datahiding techniques. The efficiency of the existing data hiding techniques did notprovide optimum performance with multiple end nodes. These issues are solvedby using Separable Data Hiding and Adaptive Particle Swarm Optimization(SDHAPSO) algorithm to attain optimal performance. Image encryption, dataembedding, data extraction/image recovery are the main phases of the proposedapproach. DFT is generally used to extract the transform coefficient matrix fromthe original image. DFT coefficients are in float format, which assists in transforming the image to integral format using the round function. After obtainingthe encrypted image by data-hider, additional data embedding is formulated intohigh-frequency coefficients. The proposed SDHAPSO is mainly utilized for performance improvement through optimal pixel location selection within the imagefor secret bits concealment. In addition, the secret data embedding capacityenhancement is focused on image visual quality maintenance. Hence, it isobserved from the simulation results that the proposed SDHAPSO techniqueoffers high-level security outcomes with respect to higher PSNR, security level,lesser MSE and higher correlation than existing techniques. Hence, enhancedsensitive information protection is attained, which improves the overall systemperformance.

Secure separable reversible data hiding of halftone image in blockchain

To realize the distributed storage and management of a secret halftone image in blockchain,a secure separable reversible data hiding(RDH)of halftone image in blockchain(SSRDHB)was proposed.A secret halftone image can be used as the original image to generate multiple share images which can be distributed storage in each point of blockchain,and additional data can be hidden to achieve management of each share image.Firstly,the secret halftone image was encrypted through Zu Chongzhi(ZUC)algorithm by using the encryption key(EK).Secondly,the method of using odd or even of share data was proposed to hide data,and a share dataset can be generated by using polynomial operation.Thirdly,multiple share images can be obtained through selecting share data,and different additional data can be hidden through controlling odd or even of share data,and additional data can be protected by using data-hiding key(DK).After sharing process,if the receiver has both keys,the halftone image can be recovered and additional data can be revealed,and two processes are separable.Experiment results show that multiple share images hidden additional data can be obtained through SSRDHB,and the halftone image can be recovered with 100%by picking any part of share images,and one additional data can be revealed with 100%by picking any one share image.