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Review of JPEG recompression forensics for color images
Hao WANG, Jinwei WANG, Xin CHENG, Jiawei ZHANG, Hao WU, Xiangyang LUO, Bin MA
Journal of Computer Applications    2025, 45 (11): 3609-3620.   DOI: 10.11772/j.issn.1001-9081.2024111614
Abstract81)   HTML1)    PDF (2091KB)(632)       Save

The JPEG (Joint Photographic Experts Group) compression is one of the most widely used image compression standards and is involved in various forensic scenarios and security models such as image operation chain forensics, image source forensics, steganography, steganalysis, and JPEG anti-forensics. Researchers have conducted extensive studies on JPEG recompression forensics based on the characteristics of JPEG images, discovering that it not only provides prior knowledge for image forensics but also can be directly applied in forensic scenarios. Therefore, JPEG recompression forensics for color images was reviewed. Firstly, the research background of recompression forensics was introduced, and recompression forensics were classified into three types: non-aligned, aligned asynchronous, and aligned synchronous. Secondly, the basic knowledge required for recompression forensics was detailed, including the JPEG compression process, convergence error, error images, and algorithm evaluation metrics. Furthermore, existing methods for each type of problem were thoroughly reviewed and systematized. Additionally, since fields such as image steganography and adversarial examples involved robustness studies related to JPEG recompression, the applications of JPEG recompression features in these domains were highlighted, and common algorithms were compared to summarize their advantages and disadvantages. Finally, open challenges and future research directions in JPEG recompression forensics were discussed.

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Compressive sensing for ultra-wideband signals based on multi-band orthogonal frequency division multiplexing
WANG Gao-bin MA She-xiang
Journal of Computer Applications    2012, 32 (07): 1820-1822.   DOI: 10.3724/SP.J.1087.2012.01820
Abstract1001)      PDF (614KB)(722)       Save
To resolve the problem of excessively high sampling rate of the Ultra-WideBand (UWB) signals, the authors proposed a Modified Parallel Segmented Compressive Sensing (MPSCS) method. In UWB communication system based on Multi-Band Orthogonal Frequency Division Multiplexing (MB-OFDM), this paper employed reconstruction algorithm based on Orthogonal Matching Pursuit (OMP) of MPSCS for compressive sampling and signal reconstruction. To compare the Bit Error Rate (BER) performance and sampling rate of MPSCS with Parallel Segmented Compressive Sensing (PSCS) and Nyquist method, simulation had been done in CM1 channel. The simulation results demonstrate that MPSCS has the advantages in BER, sampling rate and UWB signal can be accurately reconstructed by using MPSCS when the sampling rate is only 6.06% of Nyquist rate.
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Swarm hybrid algorithm for nodes optimal deployment in heterogeneous wireless sensor network
ZHANG Bin MAO Jian-lin LI Hai-ping CHEN Bo
Journal of Computer Applications    2012, 32 (05): 1228-1231.  
Abstract1326)      PDF (2598KB)(940)       Save
The coverage problem is a basic problem in the wireless sensor networks, which indicates the Quality of Service (QoS) of sensing by wireless sensor networks. A lot cover blind areas and cover redundancies will be produced, when the nodes are deployed initially in the networks. A hybrid algorithm was proposed to deploy the heterogeneous network nodes reasonably to improve the coverage ratio and reduce the cost of the nodes,which introduced the ε-target constraint method based on Particle Swarm Optimization (PSO) and Fish Swarm Algorithm (FSA). The swarm hybrid algorithm firstly set up the concept of individual center, to quickly search the best solution domain of the individuals' locations, introducing the idea of the cluster behavior and tracing cauda behavior into the PSO, and then used the PSO to find the optimized speed and optimized location of the individuals. The simulation results show that the swarm hybrid algorithm is better than the standard PSO and the standard FSA in pursuing the balance and optimization between the coverage ratio and the cost of the networks.
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