Sharpening filters could improve the image by giving it a more defined appearance. In this paper, a comparison is made between the effects of two sharpening filters on the reliability of watermarking in image watermarking in the spatial domain. These sharpening filters are the Laplacian and the high boost. These filters are applied before running the watermark recovery algorithms. The difference between the watermark information and the host image is amplified by these filters. So the watermark could be significantly better recovered using the watermark recovery algorithm. A typical correlation-based method is used as a representative of spatial domain watermarking methods. Several experiments are carried out to compare the effectiveness of these filters on a correlation-based watermarking algorithm. Keywords: Image sharpness; Laplacian filter; High Boost Filter; Digital image watermarking; Correlation-based watermarking; Spatial Domain Watermarking.1.0 IntroductionWith the expansion of the Internet, creating, copying, transmitting, and distributing digital data becomes easy. There is therefore a strong demand for reliable and secure copyright protection methods for digital data. Watermarking has been proposed as a valid solution to this problem. The purpose of watermarking is to insert additional information into digital data without visibly modifying it [1]. In watermarking algorithm design, there is always a conflict between robustness and imperceptibility. Imperceptibility is the amount of decreases in signal quality; and robustness is the ability of the watermark to remain readable after innocent or malicious signal processing operations on the watermarked image. These parameters are incompatible with each other, and they sho...... middle of paper ......, and P. Raajan. “An effective fingerprint enhancement filtering technique with a high-boost Gaussian (HBG) filter.” International Review 2, no. 11 2012.[23] Maini, Raman and Himanshu Aggarwal. “A comprehensive review of image enhancement techniques.” arXiv preprint arXiv:1003.4053 2010.[24] Papadopoulos, Athanasios, Dimitrios I. Fotiadis and Lena Costaridou. “Improved detection of microcalcification clusters in mammography using 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, p. 322-325. IEEE, 2000.[26] Gonzalez, Rafael C. and Richard E. Woods. "Digital image processing: introduction." 2002.