Focusing on image splicing detection and splicing localization, we proposed an image splicing region detection method of noise level inconsistency. In the proposed method, we utilize the double enhancement effect of the improved Laplace operator on noise, and combine the singular value decomposition to extract the local image gradient matrix and noise features from non-overlapping image blocks. Then, we use a clustering-based threshold algorithm to classify the noise features and locate the tampered regions. Compared with the existing noise-based image splicing region detection method, the proposed method has superior performance, especially when the noise difference between the splicing region and the original region is less. In addition, the proposed method is robust to content maintenance operation such as JPEG compression, Gaussian blur, Gamma correction, down sampling, and so on.