Title :
Lossless generalized-LSB data embedding
Author :
Celik, Mehmet Utku ; Sharma, Gaurav ; Tekalp, Ahmet Murat ; Saber, Eli
Author_Institution :
Electr. & Comput. Eng. Dept., Univ. of Rochester, NY, USA
Abstract :
We present a novel lossless (reversible) data-embedding technique, which enables the exact recovery of the original host signal upon extraction of the embedded information. A generalization of the well-known least significant bit (LSB) modification is proposed as the data-embedding method, which introduces additional operating points on the capacity-distortion curve. Lossless recovery of the original is achieved by compressing portions of the signal that are susceptible to embedding distortion and transmitting these compressed descriptions as a part of the embedded payload. A prediction-based conditional entropy coder which utilizes unaltered portions of the host signal as side-information improves the compression efficiency and, thus, the lossless data-embedding capacity.
Keywords :
data compression; distortion; image coding; multimedia communication; watermarking; capacity distortion curve; compression efficiency; embedded information extraction; embedding distortion; lossless generalized-least significant bit data embedding; multimedia digital watermarking; prediction-based conditional entropy coder; signal compression; Authentication; Biology computing; Biomedical imaging; Data mining; Distortion; Payloads; Propagation losses; Signal processing; Spread spectrum communication; Watermarking; Arithmetic coding; conditional entropy coding; context modeling; data embedding; data hiding; least significant bit (LSB) modification; watermark; Algorithms; Computer Graphics; Computer Security; Data Compression; Image Interpretation, Computer-Assisted; Patents as Topic; Pattern Recognition, Automated; Product Labeling; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2004.840686