基于CFA插值特性不一致的图像真伪鉴别
收稿日期: 2018-02-06
修回日期: 2018-05-17
网络出版日期: 2019-01-31
基金资助
国家自然科学基金（No.U1536109）资助
Identifying Image Authenticity Based on CFA Inconsistency of Interpolation Characteristics
Received date: 2018-02-06
Revised date: 2018-05-17
Online published: 2019-01-31
苏文煊, 方针 . 基于CFA插值特性不一致的图像真伪鉴别[J]. 应用科学学报, 2019 , 37(1) : 33 -40 . DOI: 10.3969/j.issn.0255-8297.2019.01.004
Single-sensor digital cameras generally acquire the missing color components by color filter array (CFA) interpolation. In this work, CFA interpolation characteristics are exploited to identify image forgery. Using the differences in frequency spectrum between interpolated images and ideal full color ones, the interpolation characteristics are described by block spectral change and chrominance artifacts features. The feature difference between test images and their re-interpolated version are computed as forensic features. Finally, support vector machine (SVM) is exploited to classify the authentic and tampered images using the block-wise inconsistency of forensic features. Experimental results verify effectiveness of the proposed method and its robustness against JPEG compression.
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