WATERMARKING ON COMPRESSED DATA INTEGRATING CONVOLUTION CODING IN INTEGER WAVELETS

摘要

This paper explores the scope of integer wavelets in watermarking on compressed image with the aid of convolution coding as channel coding. Convolution coding is applied on compressed host data, instead of its direct application on watermark signal as used widely for robustness improvement in conventional system. Two-fold advantages, namely flexibility in watermarking through the creation of redundancy on the compressed data as well as protection of watermark information from additive white Gaussian noise (AWGN) attack are achieved. Integer wavelet is used to decompose the encoded compressed data that leads to lossless processing and creation of correlation among the host samples due to its mathematical structure. Watermark information is then embedded using dither modulation (DM)-based quantization index modulation (QIM). The relative gain in imperceptibility and robustness performance are reported for direct watermark embedding on entropy decoded host, using repetition code, convolution code, and finally the combined use of channel codes and integer wavelets. Simulation results show that 6.24 dB (9.50 dB) improvement in document-to-watermark ratio (DWR) at watermark power 12.73 dB (16.81 dB) and 15 dB gain in noise power for watermark decoding at bit error rate (BER) of 10-2 are achieved, respectively over direct watermarking on entropy decoded data.