江西理工大学 机构 信息工程学院,江西,赣州,341000
纸质出版:2017
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任克强, 罗桃建, 喻玲娟. 基于预测失真的自适应两遍嵌入可逆图像水印[J]. 微电子学与计算机, 2017, 34(8): 87-92.
REN Ke-qiang, LUO Tao-jian, YU Ling-juan. Adaptive Two-pass Embedding Revesible Image Watermarking Algorithm Based on Prediction Distortion[J]. 2017, 34(8): 87-92.
为了解决图像隐蔽性和水印嵌入容量之间相互矛盾的问题,提出一种基于预测失真的自适应两遍嵌入可逆图像水印.首先对图像进行分块,利用方差衡量图像子块纹理性,根据纹理性设置子块嵌入强度初始值;然后对子块图像预测失真再动态调整嵌入强度;最后利用嵌入强度自适应地进行两遍嵌入水印.实验结果表明,此方法可以在高容量嵌入时有效减少图像失真;以Airplane为原始图像时,当嵌入容量是0.1bpp(bpp为每像素嵌入的比特数),峰值性噪比为54dB;当嵌入容量达到1bpp时,峰值信噪比为35dB,实现了高容量且有较高质量的可逆图像水印算法.
In order to solve the contradiction between the concealment of watermarked image and embedded watermark information capacity. A reversible image watermarking algorithm with adaptive two-pass based on prediction distortion embedding was proposed. Firstly
the image is divided into blocks
the texture complexity of the sub-blocks is measured by variance. and the initial value of sub-block embedding intensity is set according to the texture complexity. and then dynamically adjust the embedded intensity by sub-block prediction distortion. Finally
embedded watermarking is carried out by embedding intensity adaptive two-pass. The experimental results show that the proposed method can reduce image distortion effectively in high capacity embedding
when the image is Airplane
when the embedding capacity is 0.1bpp (the number of bits per pixel)
the PSNR is 54dB. When the embedded capacity reaches 1bpp
the PSNR is 35dB.A high-capacity and high-quality image reversible watermarking algorithm is implemented.
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