Detecting USM image sharpening by using CNN

Document Type

Article

Publication Date

10-1-2018

Abstract

Image sharpening is a basic digital image processing scheme utilized to pursue better image visual quality. From image forensics point of view, revealing the processing history is essential to the content authentication of a given image. Hence, image sharpening detection has attracted increasing attention from researchers. In this paper, a convolutional neural network (CNN) based architecture is reported to detect unsharp masking (USM), the most commonly used sharpening algorithm, applied to digital images. Extensive experiments have been conducted on two benchmark image datasets. The reported results have shown the superiority of the proposed CNN based method over the existed sharpening detection method, i.e., edge perpendicular ternary coding (EPTC).

Identifier

85048097389 (Scopus)

Publication Title

Signal Processing Image Communication

External Full Text Location

https://doi.org/10.1016/j.image.2018.04.016

ISSN

09235965

First Page

258

Last Page

264

Volume

68

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