Synthetic aperture radar (SAR) images due to the usage of coherent imaging systems are affected by speckle. Thus, lots of despeckling filters have been introduced up to now to suppress the speckle. Hence, objective and subjective evaluations of the denoised SAR images become necessity. Many objective evaluating estimators have been introduced to evaluate the performance of despeckling filters. However, two main problems exist when evaluating the SAR images: 1) contradiction of objective and subjective evaluations and 2) absence of the ground-truth (noiseless) SAR image of the illuminated scene. Lots of efforts had been made to introduce precise referenceless estimators for SAR images which will be compatible with subjective evaluation and the results obtained by other estimators. In this paper, we propose a new edge detector and also a new referenceless estimator called “ Extended Ratio Edge Detector” and “ E-α β ” , respectively. These algorithms are the extended version of “ Ratio Edge Detector” and “ α β ” estimator. Experiments on images obtained from RADARSAT-1 dataset showed that the proposed edge detector and the estimator outperform their previous versions of algorithms as the proposed E-α β parameter subjectively reports up to 0. 2 better results for images filtered with FANS filter in comparison with other used methods. This is also validated by β ratio and μ ratio parameters. Therefore, it is a reliable tool for objective evaluation of despeckled SAR images.