压缩感知与直方图自适应模糊图像隐写

2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2018-11-01 DOI:10.1109/ISRITI.2018.8864460

Yoga Adhy Nugraha, Irma Safitri, Ratri Dwi Atmaja

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引用次数: 1

摘要

我们提出了压缩感知(CS)和直方图自适应模糊(HAF)图像隐写系统。实验结果表明，红色层是最适合插入的颜色层，平均PSNR值为36.15912 dB。而最好的子带是在high high或HH子带，平均PSNR值为42,65717 dB。同时，隐写图像的PSNR值最高，为63,9643 dB。通过使用条形码.bmp文件作为消息图像，我们的系统可以具有BER = 0和PSNR = 30.5574 dB。我们得到BER = 0.0122，测量率为30%。

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Compressive Sensing and Histogram Adaptive Fuzzy Image Steganography

We proposed compressive sensing (CS) and histogram adaptive fuzzy (HAF) for the image steganography system. Based on our experiments, red layer is the best color layer for insertion with the acquisition of the average PSNR value of 36.15912 dB. While the best subband is in the high high or HH subband with an average PSNR value of 42,65717 dB. Meanwhile, the stego image has the highest PSNR value of 63,9643 dB. Our system can have BER = 0 and PSNR = 30.5574 dB by using the Barcode.bmp file as the message image. We have BER = 0.0122 with a measurement rate of 30%.

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2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

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