In an modern world, image encryption played an vital role to prevent our data from illegal abuser entre. Based on this, in this paper the Markovian jump neural networks for synchronization of sampled-data control systems with two additive delay components are used on the looped functional method and its direct application is applied in image encryption. On the basis of generalized Lyapunov functional approach involves the states information such as x(tk) and x(tk+1) with few slack variables and a tuning parameter are introduced . Furthermore, the sampled-data controller is designed to contain both the present and delayed state information, thereby enhancing the control performance and design flexibility. Finally by using the new technique, the several examples are highlighted in the numerical section and also the effectiveness of an image encryption is studied.