An intelligent digital colour image watermarking approach based on wavelets and general regression neural networks

Hieu V. Dang, W. Kinsner
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引用次数: 17

Abstract

In this paper, we propose a new intelligent, robust and adaptive digital watermarking technique for colour images based on the combination of discrete wavelet transform (DWT), human visual system (HVS) model and general regression neural network (GRNN). First, the RGB image is converted to YCrCb image, and then the luminance component Y is decomposed by DWT. Wavelet coefficients are then analyzed by a HVS model to select suitable coefficients for embedding the watermark. The watermark bits are embedded into the selected coefficients by training a GRNN. At the decoder, the trained GRNN is used to recover the watermark from the watermarked image. The experimental results show that our proposed approach achieves robustness and imperceptibility in watermarking.
一种基于小波和广义回归神经网络的智能数字彩色图像水印方法
本文提出了一种基于离散小波变换(DWT)、人类视觉系统(HVS)模型和广义回归神经网络(GRNN)相结合的彩色图像智能、鲁棒和自适应数字水印技术。首先将RGB图像转换为YCrCb图像,然后对亮度分量Y进行DWT分解。然后利用HVS模型对小波系数进行分析,选择合适的水印嵌入系数。通过训练GRNN将水印位嵌入到所选系数中。在解码器处,使用训练好的GRNN从水印图像中恢复水印。实验结果表明,该方法具有较好的鲁棒性和不可感知性。
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