An overview of the fundamental approaches that yield several image denoising techniques
| Main Authors: | Charmouti, Bilal; Universiti Malaysia Perlis (UniMAP), Junoh, Ahmad Kadri; Universiti Malaysia Perlis (UniMAP), Mashor, Mohd Yusoff; Universiti Malaysia Perlis (UniMAP), Ghazali, Najah; Universiti Malaysia Perlis (UniMAP), Wahab, Mahyun Ab; Universiti Malaysia Perlis (UniMAP), Wan Muhamad, Wan Zuki Azman; Universiti Malaysia Perlis (UniMAP), Yahya, Zainab; Universiti Malaysia Perlis (UniMAP), Beroual, Abdesselam; International Islamic University Malaysia |
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| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
Universitas Ahmad Dahlan
, 2019
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| Subjects: | |
| Online Access: |
http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/11301 http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/11301/7152 |
Daftar Isi:
- Digital image is considered as a powerful tool to carry and transmit information between people. Thus, it attracts the attention of large number of researchers, among them those interested in preserving the image features from any factors that may reduce the image quality. One of these factors is the noise which affects the visual aspect of the image and makes others image processing more difficult. Thus far, solving this noise problem remains a challenge for the researchers in this field. A lot of image denoising techniques have been introduced in order to remove the noise by taking care of the image features; in other words, getting the best similarity to the original image from the noisy one. However, the findings are still inconclusive. Beside the enormous amount of researches and studies which adopt several mathematical concepts (statistics, probabilities, modeling, PDEs, wavelet, fuzzy logic, etc.), there is also the scarcity of review papers which carry an important role in the development and progress of research. Thus, this review paper intorduce an overview of the different fundamental approaches that yield the several image-denoising techniques, presented with a new classification. Furthermore, the paper presents the different evaluation tools needed on the comparison between these techniques in order to facilitate the processing of this noise problem, among a great diversity of techniques and concepts.