项目名称: 基于视觉显著内容的图像半脆弱自恢复水印算法研究
项目编号: No.61202499
项目类型: 青年科学基金项目
立项/批准年度: 2013
项目学科: 计算机科学学科
项目作者: 李春雷
作者单位: 中原工学院
项目金额: 23万元
中文摘要: 针对半脆弱自恢复水印算法鲁棒性及图像恢复质量之间存在的矛盾,本课题拟对基于视觉显著内容的图像半脆弱自恢复水印算法进行深入研究。首先,研究水印信息的有效表示。拟提出基于视觉显著内容及压缩感知的水印生成方法,降低水印量,同时增加水印的容错性。其次,研究基于图像块的多比特水印嵌入及提取策略。拟提出随机分组量化的水印嵌入方法,增加算法对于合理失真的鲁棒性,并基于最小测度水印提取器,建立误码率模型,选取合适的失真补偿因子,在未遭受恶意篡改的前提下,准确提取水印位;最后,研究篡改定位、篡改类型判别及图像恢复策略。拟提出基于双向认证及聚类分割的篡改定位方法,提高篡改定位精度,并使用SVM分类器对破坏类型进行判别,针对性地选取恢复策略,重构图像显著内容。课题研究将在保证算法鲁棒性的基础上,提高图像恢复质量。同时,该课题也将为半脆弱自恢复水印研究提供新思路,并进一步提高其实际应用价值,拓宽应用前景。
中文关键词: 视觉显著型模型;随机分组量化;篡改类型判别;自恢复;鲁棒性
英文摘要: To trade off the robustness of semi fragile self-recovery watermarking algorithm and the quality of recovery, this research is to deeply study the semi fragile self-recovery algorithm of image watermarking based on visual salient contents. First, the effective representation of watermarking information is proposed. Afterwards, we propose a watermark generation method based on visual salient contents and compressive sensing, which can not only reduce the watermark amount and but also improve the fault tolerance of the generated watermark. Second, a block-wise image multi-bit watermark embedding and extraction solution is proposed. For this solution, we propose a randomly-group quantization embedding method for increasing the robustness of the algorithm to the tolerable distortion. Moreover, we propose a Bit Error Rate (BER) model via a minimum-measure-based watermark extractor, which chooses the fine-tuned distortion compensation factor to accurately extract the watermarks when the image content integrity is kept. Finally, the solutions of the tamper localization, identification, image recovery are proposed. Namely, we propose a method based on a double authentication and clustering method to increase the accuracy of tamper localization and employ a SVM classifier to identify the tamper type, and accordingly sele
英文关键词: visual saliency;randomly-group quantization;tamper identification;self-recovery;robustness