This paper presents an optimized robust digital image watermarking scheme based on Stationary Wavelet Transform (SWT) using Bat optimization Algorithm (BA) and Speed-Up Robust Feature (SURF). The proposed scheme applies high-frequency coefficients of the SWT of the host image in the BA framework to optimize watermark strength factors in the embedding process, considering relevant attacks. On the final step of this process, the SURF detector is employed on the watermarked image for getting point features used for geometric distortion correction. For watermark extracting, the primary step is to correct probable geometrical distortions, utilizing the SURF rotation and scaling invariance property, and the procedure goes on by executing the reverse of embedding phase steps. For evaluating the capabilities of the proposed algorithm, different types of image processing operations such as Gaussian filtering, scaling, rotation and salt and pepper, Poison, speckle, and Gaussian noise, have been used as attacks. According to the experimental results, the proposed combination of techniques exhibits an overall superior performance in both imperceptibility and robustness metrics in various situations compared to state-of-the-art and relevant methods.