A Review Paper : Noise Models in Digital Image Processing
Open accessAbstract
Noise is always presents in digital images during image acquisition, coding, transmission, and processing steps.Noise is very difficult to remove it from the digital images without the prior knowledge of noise model.That is why, review of noise models are essential in the study of image denoising techniques.In this paper, we express a brief overview of various noise models.These noise models can be selected by analysis of their origin.In this way, we present a complete and quantitative analysis of noise models available in digital images.
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Various noises are naturally prevalent in digital images during image acquisition, coding, transmission, and processing steps.
“Noises in digital images: various noises are naturally prevalent in digital images during image acquisition, coding, transmission, and processing steps [19].”
From MultiBench: Multiscale Benchmarks for Multimodal Representation Learning (2021) · cites this paper as [19]
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- AUTHORS Ajay Boyat is a Research scholar in Electronics & Telecommunication and Computer Engineering Department at Military College of Telecommunication Engineering (MCTE), Military Head Quarter of War (MHOW), M.P., India. He has completed B.E. in Electronics and Communication Engineering from MITS, Gwalior in 2005, M.E. in Electronics and Telecommunication Engineering from SGSITS, Indore in 2008 and Currently Pursuing Ph.D. in Electronics and Telecommunication Engineering from Devi Ahiliya University, Indore. His research interests are Image processing, Adaptive and Non-Linear Filtering, Signal Processing, Mobile adhoc and Wireless Communication networks. He has number of research papers to his credit and has supervised three Post Graduate scholar and currently supervising three Post Graduate scholars. He has 09 years of teaching experience. He is Research and Project Cordinator in Department of Electronics & Communication Engineering at Medi-Caps Institute of Technology and Management, Indore (MP), India. He is a Global member of Internet Society. Recently he won the Best paper award Rank 1 in track 5 in 2014 IEEE ICCIC from IEEE PODHIGAI and IEEE-SIPCICOM.
- Dr. Brijendra Kumar Joshi is a Professor in Electronics & Telecommunication and Computer Engineering Department at Military College of Telecommunication Engineering (MCTE), Military Head Quarter of War (MHOW), M.P., and India. Dr. Joshi, Fellow IETE India and IE(I). He is Life time Senior Member of CSI and Life Member of ISTE. He is Member of Cryptology Research Society of India (CRSI) and Member of IEEE, IEEE Communication Society and ACM (USA). He has completed B.E. in Electronics and Telecommunication Engineering from Govt. Engineering. College, Jabalpur, M.E. in Computer Science and Engineering from Indian Institute of Science, Bangalore, Ph.D. in Electronics and Telecommunication Engineering from Rani Durgavati University, Jabalpur and M. Tech. in Digital Communication from MANIT, Bhopal. His research interests are Programming Languages, Compiler Design, Digital Communications, Mobile adhoc and Wireless Sensor Networks, Signal Processing, Parallel Computing and Software Engineering. He has number of research papers to his credit and has supervised three PhD scholars and currently supervising eight PhD scholars. He has published two books on Data Structures and Algorithms with Tata McGraw-Hill. He has 30 years of teaching experience.
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- Authors
- Boyat, A. K., & Joshi, B. K.
- Affiliations
- Ministry of Defence (IN)
- Venue
- Signal & Image Processing : An International Journal
- Published
- 2015-04-30
- Volume
- 6
- Issue
- 2
- Pages
- 63-75
- ISSN
- 0976-710X (ISSN-L)
- 2229-3922
- OpenAlex
- W1958968158
- Cited by
- 418
- References
- 0
- Citations by year
- 2026: 8 · 2025: 27 · 2024: 38 · 2023: 62 · 2022: 69 · 2021: 61 · 2020: 58 · 2019: 36 · 2018: 31 · 2017: 14 · 2016: 13 · 2015: 1
- FWCI
- 17.06
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Signal & Image Processing An International Journal (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Enhancement Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Keywords
- noise models, image denoising, noise sources
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