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Published in 2018 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-018-6831-6
Abstract: Recently, the detection of median filtering (MF), which is a popular nonlinear denoising manipulation, has attracted extensive attention from researchers. Several detectors with satisfying performance have been developed, while most of them need to train…
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Keywords:
detection;
frequency residuals;
frequency;
median filtering ... See more keywords
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Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2867370
Abstract: Median filtering is one of the most common operations for image smoothing and retouching, and it is often used as a post-processing by forgers to alleviate the traces of image tampering. Hence, if the traces…
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Keywords:
filtering detection;
detection;
network median;
adversarial network ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2897761
Abstract: Median filtering, due to highly non-linear and content-preserving, has widely used in the multimedia security fields, such as anti-forensics, steganography, and steganalysis. In the past decade, many excellent algorithms have been proposed, and have solved…
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Keywords:
forensics using;
median filtering;
filtering forensics;
image ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2923000
Abstract: This paper addresses the median filtering forensics for a lossy compressed image with low resolution, which is essential for the identification of fake images and fake videos. A deep residual model with training data augmentation…
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Keywords:
deep residual;
median filtering;
filtering forensics;
image ... See more keywords
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Published in 2019 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2018.2889921
Abstract: Median filtering has received extensive attention from forensics analyzers, as a common content-preserving, smoothing, and denoising manipulation. We propose a detection scheme for median filtering of video sequences in compressed domain based on the singular…
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Keywords:
video;
forensics compressed;
median filtering;
filtering forensics ... See more keywords
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Published in 2020 at "Geophysical Prospecting"
DOI: 10.1111/1365-2478.13032
Abstract: ABSTRACT Erratic noise often has high amplitudes and a non‐Gaussian distribution. Least‐squares–based approaches therefore are not optimal. This can be handled better with non–least‐squares approaches, for example based on Huber norm which is computationally expensive.…
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Keywords:
erratic noise;
least squares;
median filtering;
noise suppression ... See more keywords