A Review Paper: Noise Models in Digital Image Processing

By Ajay Kumar Boyat, Brijendra Kumar Joshi. arXiv.org, 2015

407 citations recorded by the source corpus.

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.

Subfields: Applied Mathematics, Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/6ff31437ca7141e2be3d5d7ec08567442cc49fa9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Mathematics

1. Halil Ibrahim Aysel
2. Xiaohao Cai
3. Khaled Alomar

In Computer Vision and Pattern Recognition

1. Halil Ibrahim Aysel
2. Xiaohao Cai
3. Khaled Alomar

Citations in the corpus

• Data Augmentation in Classification and Segmentation: A Survey and New Strategies (2023, background): “The distribution of Gaussian noise is uniform throughout the signal [53].”