This paper addresses the projection errors in 3D Gaussian Splatting (3D-GS), a technique used for real-time neural rendering. The authors analyze the projection error function, which is influenced by the Gaussian mean position, and propose an optimal projection strategy to minimize these errors. The error function is minimized when the projection plane is tangent to the line connecting the Gaussian mean and the camera center. This method reduces artifacts and improves the realism of rendered images, especially in scenarios with wide-angle lenses and sparse viewpoints. Experimental results on various datasets and scenes demonstrate the effectiveness of the proposed method, showing improved quality compared to the original 3D-GS and other state-of-the-art methods. The optimal projection strategy is also adaptable to different camera models, such as fisheye cameras and panoramic images.This paper addresses the projection errors in 3D Gaussian Splatting (3D-GS), a technique used for real-time neural rendering. The authors analyze the projection error function, which is influenced by the Gaussian mean position, and propose an optimal projection strategy to minimize these errors. The error function is minimized when the projection plane is tangent to the line connecting the Gaussian mean and the camera center. This method reduces artifacts and improves the realism of rendered images, especially in scenarios with wide-angle lenses and sparse viewpoints. Experimental results on various datasets and scenes demonstrate the effectiveness of the proposed method, showing improved quality compared to the original 3D-GS and other state-of-the-art methods. The optimal projection strategy is also adaptable to different camera models, such as fisheye cameras and panoramic images.