Compressive Sensing Audio Watermarking dengan Metode LWT dan QIM

Irma Safitri, Nur Ibrahim, Herlambang Yogaswara
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引用次数: 2

Abstract

ABSTRAKPenelitian ini mengembangkan teknik Compressive Sensing (CS) untuk audio watermarking dengan metode Lifting Wavelet Transform (LWT) dan Quantization Index Modulation (QIM). LWT adalah salah satu teknik mendekomposisi sinyal menjadi 2 sub-band, yaitu sub-band low dan high. QIM adalah suatu metode yang efisien secara komputasi atau perhitungan watermarking dengan menggunakan informasi tambahan. Audio watermarking dilakukan menggunakan file audio dengan format *.wav berdurasi 10 detik dan menggunakan 4 genre musik, yaitu pop, classic, rock, dan metal. Watermark yang disisipkan berupa citra hitam putih dengan format *.bmp yang masing-masing berukuran 32x32 dan 64x64 pixel. Pengujian dilakukan dengan mengukur nilai SNR, ODG, BER, dan PSNR. Audio yang telah disisipkan watermark, diuji ketahanannya dengan diberikan 7 macam serangan berupa LPF, BPF, HPF, MP3 compression, noise, dan echo. Penelitian ini memiliki hasil optimal dengan nilai SNR 85,32 dB, ODG -8,34x10-11, BER 0, dan PSNR ∞.Kata kunci: Audio watermarking, QIM, LWT, Compressive Sensing. ABSTRACTThis research developed Compressive Sensing (CS) technique for audio watermarking using Wavelet Transform (LWT) and Quantization Index Modulation (QIM) methods. LWT is one technique to decompose the signal into 2 sub-bands, namely sub-band low and high. QIM is a computationally efficient method or watermarking calculation using additional information. Audio watermarking was done using audio files with *.wav format duration of 10 seconds and used 4 genres of music, namely pop, classic, rock, and metal. Watermark was inserted in the form of black and white image with *.bmp format each measuring 32x32 and 64x64 pixels. The test was done by measuring the value of SNR, ODG, BER, and PSNR. Audio that had been inserted watermark was tested its durability with given 7 kinds of attacks such as LPF, BPF, HPF, MP3 Compression, Noise, and Echo. This research had optimal result with SNR value of 85.32 dB, ODG value of -8.34x10-11, BER value of 0, and PSNR value of ∞.Keywords: Audio watermarking, QIM, LWT, Compressive Sensing.
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音频分解与LWT和QIM方法
本研究开发了一种压缩压缩技术,采用升华式升华方法和量化指数调制。把信号是mendekomposisi技巧之一sub-band一分为二,即sub-band低和高。QIM是一种计算或利用额外信息进行水位表计算的有效方法。水标记音频使用音频文件格式为*.wav 10秒,使用四种音乐类型,即流行、古典、摇滚和金属。黑白图像水印的插入和各自的* . bmp格式的大小32x32 64x64像素。测试是通过测量SNR、ODG、BER和PSNR的值来进行的。插入了水印,以耐久测试的音频提供7种攻击LPF、BPF HPF、MP3压缩,噪音和回声。这项研究有价值的最佳结果乔85.32分贝,ODG -8,34x10-11, BER 0, PSNR∞。关键词:水标记,QIM, LWT,压缩Sensing。ABSTRACTThis research developed Compressive Sensing (CS)为音频用Wavelet watermarking技巧用金币(把)和Quantization指数调制(QIM)方法。把一号技巧到decompose是信号进入2 sub-bands, namely sub-band低和高。QIM是个computationally efficient方法或watermarking calculation用资讯网措施。音频watermarking干得是用和* . wav格式音频文件持续10秒过去4 genres著作百科全书》的音乐,namely,经典流行、摇滚和金属。水印是inserted (in the form of black and white形象* . bmp格式每测量32x32和64x64的像素。《价值》做测试是由测量乔,ODG BER和PSNR。音频that had been inserted水印和赐予7是测试它的durability kinds of the attacks美国如此LPF BPF HPF, MP3压缩、噪音和回声。这个研究有论点与乔的最佳价值85。32分贝,ODG的公关之价值。34x10-11、个人价值的0和∞的PSNR价值。安装:watermarking音频,把QIM Compressive Sensing。
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