کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6957752 | 1451921 | 2018 | 37 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
On the fault-tolerant performance for a class of robust image steganography
ترجمه فارسی عنوان
بر روی عملکرد شکستگی مقاوم در برابر یک طبقه از استاگونوگرافی تصویر قوی
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
چکیده انگلیسی
The mainstream adaptive steganography algorithms often cannot transmit secret messages correctly when stego images suffer from JPEG compression. In this respect, researchers proposed a series of robust adaptive steganography methods based on the framework of “Compression-resistant Domain Constructing + RS-STC Codes” in previous studies. However, these methods leave behind the fault tolerance analysis, resulting in potential mistakes in extracted messages, which brings uncertainty to practical application. To solve this problem, an error model based on burst errors and STCs decoding damage is given in this manuscript, utilizing the burst error model based on Poisson distribution. Then the model is verified using the hypothesis test problem judged by the Ï2 test method. Based on the proposed model, the error conditions of received stego sequence are depicted, and the fault-tolerant performance of the robust steganography based on “Compression-resistant Domain Constructing + RS-STC Codes” is deduced, that is, the probability lower bound for RS-STCs decoding to correctly extract embedded messages. Experiments demonstrate that the practical fault-tolerant results of previous robust steganography methods consist with the theoretical derivation results, which provides a theory support for coding parameter selection and message extraction integrity to the robust steganography based on “Compression-resistant Domain Constructing + RS-STC Codes”.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 146, May 2018, Pages 99-111
Journal: Signal Processing - Volume 146, May 2018, Pages 99-111
نویسندگان
Yi Zhang, Chuan Qin, Weiming Zhang, Fenlin Liu, Xiangyang Luo,