噪声水平不一致性的图像拼接区域检测方法

针对图像拼接篡改检测与篡改定位技术进行研究，提出了一种噪声水平不一致性的图像拼接篡改定位方法.该方法利用改进的拉普拉斯算子对噪声具有双倍加强作用的特点，结合奇异值分解，提取非重叠图像块的局部图像梯度矩阵和噪声特征，然后利用基于聚类的阈值算法，对得到的特征进行分类并定位出篡改区域.与现有的基于噪声的图像拼接区域检测方法相比，所提出的方法不仅能够检测拼篡改区域，而且当拼接区域与原始区域之间的噪声差异较小时依然有效，并且对于内容保持的图像处理操作如JPEG压缩、高斯模糊、伽玛校正、下采样等是鲁棒的.

Image Splicing Region Detection Method of Noise Level Inconsistency

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.