SIAM Journal on Imaging Sciences (SIIMS) covers all areas of imaging sciences, broadly interpreted. It includes image formation, image processing, image analysis, image interpretation and understanding, imaging-related machine learning, and inverse problems in imaging; leading to applications to diverse areas in science, medicine, engineering, and other fields. The journal’s scope is meant to be broad enough to include areas now organized under the terms image processing, image analysis, computer graphics, computer vision, visual machine learning, and visualization. Formal approaches, at the level of mathematics and/or computations, as well as state-of-the-art practical results, are expected from manuscripts published in SIIMS. SIIMS is mathematically and computationally based, and offers a unique forum to highlight the commonality of methodology, models, and algorithms among diverse application areas of imaging sciences. SIIMS provides a broad authoritative source for fundamental results in imaging sciences, with a unique combination of mathematics and applications.
SIIMS covers a broad range of areas, including but not limited to image formation, image processing, image analysis, computer graphics, computer vision, visualization, image understanding, pattern analysis, machine intelligence, remote sensing, geoscience, signal processing, medical and biomedical imaging, and seismic imaging. The fundamental mathematical theories addressing imaging problems covered by SIIMS include, but are not limited to, harmonic analysis, partial differential equations, differential geometry, numerical analysis, information theory, learning, optimization, statistics, and probability. Research papers that innovate both in the fundamentals and in the applications are especially welcome. SIIMS focuses on conceptually new ideas, methods, and fundamentals as applied to all aspects of imaging sciences.
The journal also features survey articles in emerging fields that convey the essential information of that field to a broad audience and foster cross-disciplinary collaborations.
To be considered by the journal, a paper should be in one (or a combination) of the following categories:
- papers that develop new mathematical models and ideas for critical problems in the broad area of imaging sciences
- papers that analyze existing fundamental models or computational methods being applied to the broad area of imaging sciences
- papers that develop new computational methods relevant to the broad area of imaging sciences
- papers devoted to direct numerical simulations or to experimental study of fundamental mathematical and/or computational frameworks leading to state-of-the-art results in the broad area of imaging sciences
Although the journal has no formal limits on manuscript length, papers exceeding 30 journal pages, excluding the supplementary materials, will be reviewed more closely to ensure that the excess is fully justified. See Instructions for Authors for additional details.
Submission of a manuscript to a SIAM journal is representation by the author that the manuscript has not been submitted simultaneously for publication elsewhere. Papers that have been published elsewhere will not be considered. An exception may be made for a substantially revised conference proceedings paper, provided that it is so identified in the submission letter and in the paper itself.