An Efficient Watermarking Method Based on Significant Difference of Wavelet Coefficient Quantization

• Published in: IEEE transactions on multimedia Vol. 10; no. 5; pp. 746 - 757
• Main Authors: LIN, Wei-Hung, HOMG, Shi-Jinn, KAO, Tzong-Wann, PINGZHI FAN, LEE, Cheng-Ling, YI PAN
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2008; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Artificial intelligence; Blind; Blocking; Coefficients; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Copyright protection; Exact sciences and technology; Extraction; Filtering; Gaussian noise; Image coding; Low pass filters; Memory and file management (including protection and security); Memory organisation. Data processing; Pattern recognition. Digital image processing. Computational geometry; PSNR; Quantization; significant coefficient difference; Software; Studies; Thresholds; Transform coding; watermark; Watermarking; Wavelet; Wavelet coefficients; Wavelet transforms; Multimedia; Blind; watermark; significant coefficient difference; Stéganography; Image compression; Adaptive method; Copyright; Gaussian noise; Wavelet transformation; Signal quantization; Intellectual property; copyright protection; wavelet; Low pass filter; Safety; Digital watermarking
• ISSN: 1520-9210; 1941-0077
• DOI: 10.1109/TMM.2008.922795

This paper proposes a blind watermarking algorithm based on the significant difference of wavelet coefficient quantization for copyright protection. Every seven nonoverlap wavelet coefficients of the host image are grouped into a block. The largest two coefficients in a block are called significant coefficients in this paper and their difference is called significant difference. We quantized the local maximum wavelet coefficient in a block by comparing the significant difference value in a block with the average significant difference value in all blocks. The maximum wavelet coefficients are so quantized that their significant difference between watermark bit 0 and watermark bit 1 exhibits a large energy difference which can be used for watermark extraction. During the extraction, an adaptive threshold value is designed to extract the watermark from the watermarked image under different attacks. We compare the adaptive threshold value to the significant difference which was quantized in a block to determine the watermark bit. The experimental results show that the proposed method is quite effective against JPEG compression, low-pass filtering, and Gaussian noise; the PSNR value of a watermarked image is greater than 40 dB.