由于有功能強(qiáng)大的計(jì)算機(jī)和圖像處理軟件的存在，普通用戶可以將數(shù)字圖像篡改成他
們想得到的任何形式。所以檢測(cè)數(shù)字篡改變成了一個(gè)非常嚴(yán)峻的問(wèn)題。在大多數(shù)情況下，數(shù)字篡改圖像是很逼真的，但是在處理過(guò)程中也會(huì)留下一些痕跡。文章將圖像的模糊估計(jì)和傳感器的模板噪聲檢測(cè)篡改的方法結(jié)合起來(lái)，對(duì)多幅圖像操作，實(shí)驗(yàn)證明有不錯(cuò)的檢測(cè)效果。
關(guān)鍵字：篡改圖像；模糊估計(jì)；傳感器噪聲；檢測(cè)篡改；模板噪聲
Abstract:With powerful computer and editing software, ordinary users could turn digital images into what they want. The detecting of digital tampering has become a crucial problem. In most of the time,digital tampering is not perceptible by human, but some traces of digital tampering may be left in the media during the process. This article uses blur estimation and sensor noise to detect forgery. The performance of the proposed method is demonstrated on several forged images and has been proved to have good effect.
Keywords: Image Forgery; Blur Estimation; Sensor Noise; Detect Forgery; Pattern Noise