With the development of digital information technologies, robust watermarking framework is taken into real consideration as a challenging issue in the area of image processing, due to the large applicabilities and its utilities in a number of academic and real environments. There are a wide range of solutions to provide image watermarking frameworks, while each one of them is attempted to address an efficient and applicable idea. In reality, the traditional techniques do not have sufficient merit to realize an accurate application. Due to the fact that the main idea behind the approach is organized based on contourlet representation, the only state-of-the-art materials that are investigated along with an integration of the aforementioned contourlet representation in line with watermarking framework are concentrated to be able to propose the novel and skilled technique. In a word, the main process of the proposed robust watermarking framework is organized to deal with both new embedding and de-embedding processes in the area of contourlet transform to generate watermarked image and the corresponding extracted logo image with high accuracy. In fact, the motivation of the approach is that the suggested complexity can be of novelty, which consists of the contourlet representation, the embedding and the corresponding de-embedding modules and the performance monitoring including an analysis of the watermarked image as well as the extracted logo image. There is also a scrambling module that is working in association with levels-directions decomposition in contourlet embedding mechanism, while a decision maker system is designed to deal with the appropriate number of sub-bands to be embedded in the presence of a series of simulated attacks. The required performance is tangibly considered through an integration of the peak signal-to-noise ratio and the structural similarity indices that are related to watermarked image. And the bit error rate and the normal correlation are considered that are related to the extracted logo analysis, as well. Subsequently, the outcomes are fully analyzed to be competitive with respect to the potential techniques in the image colour models including hue or tint in terms of their shade, saturation or amount of gray and their brightness via value or luminance and also hue, saturation and intensity representations, as long as the performance of the whole of channels are concentrated to be presented. The performance monitoring outcomes indicate that the proposed framework is of significance to be verified.