This work introduces a four-step iterative scheme for approximating fixed points of E-enriched nonexpansive mappings in uniformly convex Banach spaces. Theoretical analysis establishes a strong convergence under suitable assumptions on the mapping or the underlying space. To demonstrate its practical relevance, the scheme is applied to an image restoration problem formulated within a fixed-point framework. The numerical results show stable reconstructions with enhanced PSNR and SNR values, indicating superior performance in handling inverse imaging tasks. These findings underline both the theoretical strength and the computational efficiency of the proposed approach.