基于客观图像质量指标的嵌套水印方案性能评价

Priya R Sankpal, P. Vijaya
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引用次数: 0

摘要

在这个数字时代,互联网的广泛使用导致图像在开放网络的处理和传输过程中受到各种各样的失真。对于水印应用,将水印图像的质量与原始图像进行比较。在过去十年的文献中,使用了许多性能度量,包括主观和客观质量度量。与客观图像质量度量相比,主观图像质量度量通常耗时且昂贵。本文尝试研究嵌套水印方案的性能度量和客观图像质量指标,包括峰值信噪比(PNSR)、均方误差(MSE)、相关系数(CC)、归一化相关系数(NCC)和结构相似度指数(SSIM)。对于所提出的嵌套水印方法,使用四个频带的离散小波变换(DWT)和奇异值(SVD)组合对这些客观图像质量指标进行评估。客观指标的性能可以根据其对水印伪影的敏感性来判断。从获得的结果可以清楚地看出,对于大多数水印应用程序,SSIM提供了更好的洞察所使用算法的性能,其中PNSR对于某些水印工件失败。本文的研究结果是基于基于DICOM图像数据库的嵌套水印算法实验得出的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Evaluation of Nested Watermarked Scheme using Objective Image Quality Metrics
In this digital era, extensive usage of internet has resulted in images being subjected to various distortions during processing and transmitting over open networks. For watermarking applications, watermarked image quality is evaluated in comparison to the original image. In the last decade literature, many performance metrics have been used, comprising of both subjective and objective quality metrics. The subjective image quality metrics are generally time consuming and expensive in contrast to objective image quality metrics. This paper, attempted an investigation for measuring performance of nested watermarking schemes and objective image quality metrics which included Peak signal to Noise Ratio (PNSR), Mean Square Error (MSE), Correlation Coefficient (CC), Normalized Correlation Coefficient (NCC) and Structural Similarity Index (SSIM). For the proposed nested watermarking method, these objective image quality metrics were evaluated using combination of Discrete Wavelet Transforms (DWT) and Singular values (SVD) in the four frequency bands. Performance of objective metrics can be judged based on the their sensitiveness to watermarking artifacts. It is clear from the results obtained, for most watermarking applications SSIM provides better insight into the performance of the algorithm used where as PNSR fails for certain watermark artifacts. Findings drawn in this paper are based on the experimentation of nested watermarking algorithm using a DICOM image database.
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