Low-light image enhancement aims to restore under-exposed images captured in dark scenarios. Traditional frame-based cameras often fail to capture structure and color information due to exposure time limitations, while event cameras, with their high dynamic range (HDR) and asynchronous response to brightness changes, excel in extreme low-light conditions. Inspired by the Retinex theory, we propose ERetinex, the first framework combining Retinex theory with event cameras for low-light image restoration. Our method leverages event cameras' high temporal resolution to accurately estimate scene illumination and fuses HDR data with traditional image color information to enhance image quality. Experimental results show that ERetinex outperforms state-of-the-art methods, achieving a 1.0613 dB gain in PSNR while reducing FLOPS by 84.28%.