IEEE Transactions on Image Processing
Published by IEEE
ISSN : 1057-7149
Abbreviation : IEEE Trans. Image Process.
Aims & Scope
The IEEE Transactions on Image Processing covers novel theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications.
Topics of interest include, but are not limited to, the mathematical, statistical, and perceptual modeling, representation, formation, coding, filtering, enhancement, restoration, rendering, halftoning, search, and analysis of images, video, and multidimensional signals.
Applications of interest include image and video communications, electronic imaging, biomedical imaging, image and video systems, and remote sensing.
View Aims & ScopeMetrics & Ranking
Impact Factor
Year | Value |
---|---|
2025 | 13.7 |
Journal Rank
Year | Value |
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2024 | 956 |
Journal Citation Indicator
Year | Value |
---|---|
2024 | 25095 |
SJR (SCImago Journal Rank)
Year | Value |
---|---|
2024 | 2.502 |
Quartile
Year | Value |
---|---|
2024 | Q1 |
h-index
Year | Value |
---|---|
2024 | 346 |
Impact Factor Trend
Abstracting & Indexing
Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.
Subjects & Keywords
Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.
Most Cited Articles
The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.
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Image quality assessment: from error visibility to structural similarity
Citation: 43818
Authors: A.C., H.R., E.P.
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Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
Citation: 7240
Authors: Kostadin, Alessandro, Vladimir, Karen
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Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Citation: 6621
Authors: Kai, Wangmeng, Yunjin, Deyu, Lei
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No-Reference Image Quality Assessment in the Spatial Domain
Citation: 4676
Authors: A., A. K., A. C.
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Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
Citation: 4193
Authors: Michael, Michal