A simultaneous despeckling and enhancing of synthetic aperture radar (SAR) images seem complex as speckle interventions are not entirely irrelevant components. As a consequence, the restoration needs to be carefully performed. Therefore, in this paper, a fractional-order total variation regularization is introduced into the popular variational retinex framework to address the speckle reduction and enhancement requirement of SAR imagery. Based on the widespread assumption that speckles follow a gamma distribution, the data fidelity term is redesigned in the proposed model. The fast numerical optimization technique named Split-Bregman scheme is used for an improved computational efficiency. In light of the results obtained, the use of fractional-order gradient has shown a significant improvement in preserving the details in the comparative analysis. Furthermore, the enhancement obtained under the proposed framework is superior to the other comparative methods, as observed from the results.