<p>The primary objective of the watermarking framework in the present research is to develop a novel integration of singular vector decomposition, discrete cosine transform (DCT), and contourlet representation, while advanced methods focus on providing new techniques. It should be noted that the main process of the proposed watermarking framework is designed to be compatible with new embedding and de-embedding approaches in the unique areas of singular vector decomposition and contourlet representation, so that watermarked images and the corresponding extracted logo images are obtained with high accuracy. In fact, the motivation behind this approach is the combination of DCT, singular vector decomposition (SVD), and contourlet, where contourlet is applied to the host image. After partitioning the coefficients into small blocks, a digital cosine transform is performed. Next, by selecting appropriate coefficients and applying SVD, the desired logo is inserted, and in the reverse process, the watermarked image is obtained. The extraction module is also implemented correspondingly, in a unique manner. Finally, a set of simulated attacks is presented to evaluate the performance of the proposed method, which is assessed based on several evaluation factors, including normal correlation, bit error rate, peak signal-to-noise ratio, and structural similarity. The results of the proposed watermarking framework demonstrate better performance than that of state-of-the-art methods.</p>