Comparison between the Effect of Laplacian and High Boost Filters on Spatial Domain Watermarking

Comparison between the Effect of Laplacian and High Boost Filters on Spatial Domain Watermarking

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The sharpening filters could boost the image by changing it look more defined. In this paper, a comparison is toke place between the effects two sharpening filters on the reliability of the watermark in spatial domain image watermarking. These sharpening filters are the Laplacian and the high boost. These filters are applied before preforming watermark recovery algorithms. The difference between the watermark information and host image is amplified by these filters. Thus, watermark could recover considerably better by watermark recovery algorithm. A typical correlation based method is used as a representative of spatial domain watermarking methods. Several experiments are done to compare the effectiveness of these filters on correlation based watermarking algorithm.
Keywords: Image Sharpening; Laplacian Filter; High Boost Filter; Digital Image Watermarking; Correlation Based Watermarking; Spatial Domain Watermarking.
1.0 Introduction
With the expansion of the Internet, create the copy, transmit, and distribute the digital data becomes easy. Therefore, there is the high demand for trustworthy and secure copyright protection methods for digital data. The watermarking has been proposed as a valid solution for this problem. The purpose of the watermark is to insert some extra information about the digital data without visibly modifying it [1].
In the design of the watermarking algorithm always, there is a conflict between robustness and imperceptibility. The imperceptibility is the amount of decreases in signal quality; and the robustness is the ability of the watermark to persist readable after innocent or malicious signal processing operations on the watermarked image. These parameters are incompatible with each other, and they sho...

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..., and P. Raajan. "An Efficient Finger Print Enhancement Filtering Technique with High Boost Gaussian Filter (HBG)." International Journal 2, no. 11 2012.
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[24] Papadopoulos, Athanasios, Dimitrios I. Fotiadis, and Lena Costaridou. "Improvement of microcalcification cluster detection in mammography utilizing image enhancement techniques." Computers in biology and medicine 38, no. 10: 1045-1055, 2008.
[25] Greenberg, Shlomo, Mayer Aladjem, Daniel Kogan, and Itshak Dimitrov. "Fingerprint image enhancement using filtering techniques." In Pattern Recognition, 2000. Proceedings. 15th International Conference on, vol. 3, pp. 322-325. IEEE, 2000.
[26] Gonzalez, Rafael C., and Richard E. Woods. "Digital Image Processing: Introduction." 2002.

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