Image enhancement plays a crucial role in improving the visual quality of images for various applications, including medical imaging, surveillance, and computer vision. This work proposes a novel image enhancement method based on guided filtering and adaptive gamma correction to address the limitations of conventional approaches. The existing method relies on bilateral filtering and fixed gamma correction, which may not effectively preserve fine details and contrast in complex scenes. The proposed method replaces bilateral filtering with guided filtering for improved edge preservation and introduces adaptive gamma correction to dynamically enhance image contrast. The experimental results demonstrate that the proposed method achieves a significant reduction in Mean Squared Error (MSE) and an increase in Peak Signal-to-Noise Ratio (PSNR) across multiple test images. The results confirm the effectiveness of the proposed approach in achieving better visual quality while maintaining structural similarity.