To address the problems of the inferior localization and high probability of false rejection in existing self-recovery fragile watermarking algorithms, this paper proposes a new self-recovery fragile watermarking sche...To address the problems of the inferior localization and high probability of false rejection in existing self-recovery fragile watermarking algorithms, this paper proposes a new self-recovery fragile watermarking scheme with superior localization, and further discusses the probability of false rejection （PFR） and the probability of false acceptance （PFA） of the proposed scheme. Moreover, four measurements are defined to evaluate the quality of a recovered image. In the proposed algorithm, the original image is divided into 2×2 blocks to improve localization precision and decrease PFR under occurrence of random tampering. The PFR under occurrence of region tampering can be effectively decreased by randomly embedding the watermark of each block in conjunction with a novel method of tamper detection. Compared with the current self-recovery fragile watermarking algorithms, the proposed scheme not only resolves the tamper detection problem of self-embedding watermarking, but also improves the robustness against the random tampering of self-embedding watermarking. In addition, the subjective measurements are provided to evaluate the performance of the self-recovery watermarking schemes for image authentication.展开更多
We present a method for detecting oil spills in a complex scene of SAR imagery,including segmenting oil spills,and avoiding false alarms.Segmentation is carried out using a multi-time and multi-hierarchical method by ...We present a method for detecting oil spills in a complex scene of SAR imagery,including segmenting oil spills,and avoiding false alarms.Segmentation is carried out using a multi-time and multi-hierarchical method by dividing the complex sea surface into bright sea and dark sea.Gray-based and edge-based segmentations are done to extract oil spills from bright and dark sea,respectively.The proposed method can extract complete oil spills,obtain better visual results,and increase detection probability more accurately than the traditional method.Based on the surrounding features and the oil spills’features,dark land spots and low contrast dark spots are removed efficiently,thus reducing false alarms.The experimental results demonstrate that the proposed algorithm has fast computation speed,high detection accuracy,and is very useful and effective for detecting oil spills in SAR imagery.展开更多
基金the Program for New Century Excellent Talents in University of China (Grant No.NCET-05-0794)Southwest Jiaotong University Doctors Innovation Funds (2007)Application Basic Foundation of Sichuan Province, China (Grant No.2006 J13-10-5)
文摘To address the problems of the inferior localization and high probability of false rejection in existing self-recovery fragile watermarking algorithms, this paper proposes a new self-recovery fragile watermarking scheme with superior localization, and further discusses the probability of false rejection （PFR） and the probability of false acceptance （PFA） of the proposed scheme. Moreover, four measurements are defined to evaluate the quality of a recovered image. In the proposed algorithm, the original image is divided into 2×2 blocks to improve localization precision and decrease PFR under occurrence of random tampering. The PFR under occurrence of region tampering can be effectively decreased by randomly embedding the watermark of each block in conjunction with a novel method of tamper detection. Compared with the current self-recovery fragile watermarking algorithms, the proposed scheme not only resolves the tamper detection problem of self-embedding watermarking, but also improves the robustness against the random tampering of self-embedding watermarking. In addition, the subjective measurements are provided to evaluate the performance of the self-recovery watermarking schemes for image authentication.
基金supported by the National Natural Science Foundation of China(Grant Nos.61171194,61120106004)"111"Project of China(Grant No.B14010)
文摘We present a method for detecting oil spills in a complex scene of SAR imagery,including segmenting oil spills,and avoiding false alarms.Segmentation is carried out using a multi-time and multi-hierarchical method by dividing the complex sea surface into bright sea and dark sea.Gray-based and edge-based segmentations are done to extract oil spills from bright and dark sea,respectively.The proposed method can extract complete oil spills,obtain better visual results,and increase detection probability more accurately than the traditional method.Based on the surrounding features and the oil spills’features,dark land spots and low contrast dark spots are removed efficiently,thus reducing false alarms.The experimental results demonstrate that the proposed algorithm has fast computation speed,high detection accuracy,and is very useful and effective for detecting oil spills in SAR imagery.
