In　this　paper,　we　propose　a　new　method　to　detect　the　forgeries　in　digital　images　by　using　photo-response　non-uniformity　(PRNU)　noise　features.　The　method　utilizes　canonical　correlation　analysis　(CCA)　to　measure　linear　correlation　relationship　between　two　sets　of　PRNU　noise　estimation　from　images　taken　by　the　same　camera.　The　linear　correlation　relationship　maximizes　the　correlation　between　the　noise　reference　pattern(or　PRNU　noise　estimation)　and　PRNU　noise　features　from　the　same　camera.　To　further　improve　the　detection　accuracy　rate,　the　difference　of　variance　between　an　image　region　and　its　smoothed　version　is　used　to　categorize　the　image　region　into　heavily　textured　region　class　or　non-heavily　textured　region　class.　For　a　heavily　textured　region　or　a　non-heavily　textured　region,　Neyman-Pearson　decision　is　used　to　calculate　the　corresponding　threshold,　and　get　the　final　result　of　detection.　©　2010　IEEE.