This work investigates the improvement of digital watermark detection robustness by applying image sharpening prior to the detection stage for an algorithm through the use of DCT-domain for both embedding and detection. Watermark detection is treated as a binary classification problem, enabling the use of the recall metric to evaluate the quality of detection. The recall metric is calculated on a set of test images by embedding and detecting the watermark with unsharp masking applied as a pre-filtering step. A method for selecting the optimal sharpening strength coefficient is proposed, based on maximizing the recall metric under fixed embedding and detection parameters. Computational experiments across a range of distortions demonstrate that pre-filtering with the optimal sharpening strength coefficient determined by the proposed method increases the true positive detection rate for most tested distortions without increasing the number of false positive detections.