Evidence map›Paper›PMID 35872932›Full record

ArticleComputational and mathematical methods in medicine2022

Deep Image Watermarking to JPEG Compression Based on Mixed-Frequency Channel Attention.

Jun Tan, Yinan Hu, Ziming Shi, Bin Wang

RetractedAbstract readRetracted Publication
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Jun TanThe Key Laboratory of Advanced Design and Intelligent Computing, School of Software Engineering, Dalian University, Dalian 116622, China.ORCID https://orcid.org/0000-0001-7889-9691
Yinan HuThe Key Laboratory of Advanced Design and Intelligent Computing, School of Software Engineering, Dalian University, Dalian 116622, China.
Ziming ShiDalian University Experimental Center, Dalian University, Dalian 116622, China.ORCID https://orcid.org/0000-0001-9284-4654
Bin WangThe Key Laboratory of Advanced Design and Intelligent Computing, School of Software Engineering, Dalian University, Dalian 116622, China.ORCID https://orcid.org/0000-0002-8800-000X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep blind watermarking algorithms based on an end-to-end encoder-decoder architecture have recently been extensively studied as an important technology for protecting copyright. However, none of the existing algorithms can fully utilize the channel features of the image to improve the robustness against JPEG compression while obtaining high visual quality. Therefore, we propose firstly a mixed-frequency channel attention method in the encoder, which utilizes different frequency components of the 2D-DCT domain as weight coefficients during channel squeezing and excitation. Its essence is to suppress the useless feature maps and enhance the feature maps suitable for watermarking embedding by introducing frequency analysis in the channel dimension. The experimental results indicate that the PSNR of our method reaches over 38 and the BER is less than 0.01% under the JPEG compression with quality factor

Indexed as

Data CompressionImage Interpretation, Computer-AssistedAlgorithmsAttentionHumansNormal Distribution

Identifiers

PMID35872932
PMCPMC9303108

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.