IET Image Processing

Aims & Scope

The range of topics covered by IET Image Processing includes the following areas related to the generation, processing and communication of visual information: Generation and Display - Imaging sensors and acquisition systems, illumination, sampling and scanning, quantization, colour reproduction, image rendering, display and printing systems, evaluation of image quality.

Processing and Analysis - Image enhancement, restoration, segmentation, registration, multispectral, colour and texture processing, multiresolution processing and wavelets, morphological operations, stereoscopic and 3-D processing, motion detection and estimation, video and image sequence processing.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)
• Web of Science

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Engineering, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Copyright url
• Plagiarism url
• Preservation url
• Apc url
• License

Plagiarism Policy

This journal follows a plagiarism policy. All submitted manuscripts are screened using reliable plagiarism detection software to ensure originality and academic integrity. Authors are responsible for proper citation and acknowledgment of all sources, and any form of plagiarism, including self-plagiarism, will not be tolerated.

For more details, please refer to our official: Plagiarism Policy.

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Computer Science and Engineering, ensuring accessibility and quality in research dissemination.

This journal does not charge a mandatory Article Processing Charge (APC). However, optional open access publication may incur fees based on the publisher’s policies.

Explore journals without APCs for alternative publishing options.

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.

• Medical image segmentation using deep learning: A survey

  Citation: 580

  Authors: Risheng, Tao, Ruixia, Bingtao, Hongying, Asoke K.

• Retinal vessel segmentation by improved matched filtering: evaluation on a new high‐resolution fundus image database

  Citation: 377

  Authors: Jan, Radim, Attila, Joachim, Jiri, Jiri, Tomas, Pavel, Ondrej, Elli

• Simultaneous image fusion and denoising with adaptive sparse representation

  Citation: 307

  Authors: Yu, Zengfu

• Classification of malignant melanoma and benign skin lesions: implementation of automatic ABCD rule

  Citation: 212

  Authors: Reda, Karim

• Combination of contrast limited adaptive histogram equalisation and discrete wavelet transform for image enhancement

  Citation: 164

  Authors: Huang, Zhao, Wang, Sun

• Semi‐automatic leaf disease detection and classification system for soybean culture

  Citation: 161

  Authors: Sukhvir, Shreelekha, Shivani

• Block‐based discrete wavelet transform‐singular value decomposition image watermarking scheme using human visual system characteristics

  Citation: 153

  Authors: Nasrin M., Bee Ee, Taha H.

• Change detection in SAR images using deep belief network: a new training approach based on morphological images

  Citation: 152

  Authors: Farnaam, Gholamreza, Hooman

• Multi‐focus image fusion based on non‐subsampled shearlet transform

  Citation: 149

  Authors: Gao, Xu, Feng

• Recognizing apple leaf diseases using a novel parallel real‐time processing framework based on MASK RCNN and transfer learning: An application for smart agriculture

  Citation: 130

  Authors: Zia ur, Muhammad Attique, Fawad, Robertas, Syed Rameez, Wasif, Kashif