© 2021 IEEEA digital image can be easily manipulated in today’s rapidly boosting technology. Among different types of image forgery methods, Copy-move forgery (CMF) is one of the most popular forgery methods in which a part of the image is copied and pasted into the same image or a different image. Therefore, the development of forgery detection methods has become a hot topic for both researchers and practitioners. In this study, a new CMF method combined with Discrete Cosine Transform (DCT) and optimum parameter Bilateral Filtering (OBF) is proposed to detect copied areas in a digital image. The visual and quantitative comparisons of the proposed hybrid method (DCT-OBF) have been made with traditional DCT based methods. The proposed method outperformed the former bilateral based method as well as the DCT based methods in terms of visual and quantitative analysis. Moreover, comparisons with conventional block-based methods have been carried out for different post-processing attacks such as image blurring and contrast adjustment. Quantitative comparisons demonstrate that the proposed method is better than the conventional block based methods, especially for post-processed images. For blurring post-processed images, the proposed method have provided higher Precision (18% improvement), F1 score (13% improvement), and Recall (5% improvement) rates than the former block based methods.