Conference Proceeding

Image Quality Metrics: PSNR vs. SSIM.

01/2010; DOI:10.1109/ICPR.2010.579 In proceeding of: 20th International Conference on Pattern Recognition, ICPR 2010, Istanbul, Turkey, 23-26 August 2010
Source: DBLP

ABSTRACT In this paper, we analyse two well-known objective image quality metrics, the peak-signal-to-noise ratio (PSNR) as well as the structural similarity index measure (SSIM), and we derive a simple mathematical relationship between them which works for various kinds of image degradations such as Gaussian blur, additive Gaussian white noise, jpeg and jpeg2000 compression. A series of tests realized on images extracted from the Kodak database gives a better understanding of the similarity and difference between the SSIM and the PSNR.

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    ABSTRACT: There are several digital watermarking metrics proposed by researchers. These metrics can determine the robustness and the imperceptibility of watermarking schemes discretely. Here, there is a lack of an effective strategy to evaluate the balanced trade-off between these requirements. Meanwhile, it is hardly possible to determine crisp thresholds to limit the acceptable and unacceptable boundaries for robustness and imper-ceptibility. Hence, it is difficult to obtain an accurate mathematical model in order to evaluate the degree of trade-off between watermarking requirements. Thus, it is most advantageous to adopt the fuzzy-based model to fulfill this need. This paper develops a fuzzy inference system (FIS) effectively for exploring the performance trade-off among watermarking performance requirements. We implemented this technique to evaluate EISB (Enhanced Intermediate Significant Bit) watermarking scheme. We also focused on different intensities of Reset Removal Attack which were less considered before, by other researchers. Two main contributions of this paper are the performance fuzzy model itself, and the performance analysis of this model which was carried out and confirmed by results via simulation.
    International journal of innovative computing, information & control: IJICIC 08/2012; 8(7):5067-5081. · 2.93 Impact Factor


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Alain Horé