Feng Liu

Dr. Feng Liu

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 October 2017 in Information
Verified
Journal Article
Open access
PDF file
FLFeng Liu
Feng Liu
MHMiguel Hernandez-Cabronero
Miguel Hernandez-Cabronero
VSVictor Sanchez
Victor Sanchez
MMMichael W. Marcellin
Michael W. Marcellin
ABAli Bilgin
Ali Bilgin
With the increasing utilization of medical imaging in clinical practice and the growing dimensions of data volumes generated by various medical imaging modalities, the distribution, storage, and management of digital medical image data sets requires data compression. Over the past few decades, several image compression standards have been proposed by international standardization organizations. This paper discusses the current status of these image compression standards in medical imaging applications together with some of the legal and regulatory issues surrounding the use of compression in medical settings.

25 September 2018 in Artificial Intelligence in Medicine
Verified
Journal Article
Closed access
MNMuhammad Khalid Khan Niazi
Muhammad Khalid Khan Niazi
YLY. Lin
Y. Lin
FLFeng Liu
Feng Liu
AAA. Ashok
A. Ashok
MMM.W. Marcellin
M.W. Marcellin
ABA. Bilgin
A. Bilgin

30 November 2022 in Computers in Biology and Medicine
Verified
Journal Article
Closed access
RCRongsheng Cui
Rongsheng Cui
RYRunzhuo Yang
Runzhuo Yang
FLFeng Liu
Feng Liu
HGHua Geng
Hua Geng

1 July 2020 in Electronics Letters
Verified
Journal Article
Open access
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SZShuang Zhang
Shuang Zhang
FLFeng Liu
Feng Liu
The fusion of infrared and visible images has been playing an important role in various scenarios all over the world. For the fusion results from most of the existing techniques in this area, some features, such as the image contrast and edge details, are still needed to be improved. In this Letter, a new fusion method of the infrared and visible image is rendered. In this method, the infrared image is preprocessed to improve the contrast. Then, the two source images are decomposed based on non‐subsampled shearlet transform (NSST). The fusion rules based on regional energy and co‐occurrence filtering are proposed for the low‐frequency and high‐frequency NSST coefficients, respectively. Experimental results show that the proposed method can effectively retain the details of the source image, meanwhile improve the contrast of the fused image.

13 March 2023 in Signal Processing: Image Communication
Verified
Journal Article
Closed access
YJYinghai Jiang
Yinghai Jiang
RCRongsheng Cui
Rongsheng Cui
FLFeng Liu
Feng Liu

30 November 2022 in Biomedical Signal Processing and Control
Verified
Journal Article
Closed access
GSGuiling Sun
Guiling Sun
XRXiangnan Ren
Xiangnan Ren
ZWZhihong Wang
Zhihong Wang
FLFeng Liu
Feng Liu