Supporting ANFIS interpolation for image super resolution with fuzzy rough feature selection Article Swipe
Muhammad Ismail
,
Changjing Shang
,
Jing Yang
,
Qiang Shen
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s10489-024-05445-7
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s10489-024-05445-7
Image Super-Resolution (ISR) is utilised to generate a high-resolution image from a low-resolution one. However, most current techniques for ISR confront three main constraints: i) the assumption that there is sufficient data available for training, ii) the presumption that areas of the images concerned do not involve missing data, and iii) the development of a computationally efficient model that does not compromise performance. In addressing these issues, this study proposes a novel lightweight approach termed Fuzzy Rough Feature Selection-based ANFIS Interpolation (FRFS-ANFISI) for ISR. Popular feature extraction algorithms are employed to extract the potentially significant features from images, and population-based search mechanisms are utilised to implement effective FRFS methods that assist in selecting the most important features among them. Subsequently, the processed data is entered into the ANFIS interpolation model to execute the ISR operation. To tackle the sparse data challenge, two adjacent ANFIS models are trained with sufficient data where appropriate, intending to position the ANFIS model of sparse data in the middle. This enables the two neighbouring ANFIS models to be interpolated to produce the otherwise missing knowledge or rules for the model in between, thereby estimating the corresponding outcomes. Conducted on standard ISR benchmark datasets while considering both sufficient and sparse data scenarios, the experimental studies demonstrate the efficacy of the proposed approach in helping deal with the aforementioned challenges facing ISR.
Related Topics
Concepts
Computer science
Interpolation (computer graphics)
Adaptive neuro fuzzy inference system
Artificial intelligence
Pattern recognition (psychology)
Feature selection
Feature (linguistics)
Image (mathematics)
Fuzzy logic
Image scaling
Selection (genetic algorithm)
Computer vision
Image processing
Fuzzy control system
Linguistics
Philosophy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s10489-024-05445-7
- https://link.springer.com/content/pdf/10.1007/s10489-024-05445-7.pdf
- OA Status
- hybrid
- Cited By
- 1
- References
- 45
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4394976453
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4394976453Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s10489-024-05445-7Digital Object Identifier
- Title
-
Supporting ANFIS interpolation for image super resolution with fuzzy rough feature selectionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-04-01Full publication date if available
- Authors
-
Muhammad Ismail, Changjing Shang, Jing Yang, Qiang ShenList of authors in order
- Landing page
-
https://doi.org/10.1007/s10489-024-05445-7Publisher landing page
- PDF URL
-
https://link.springer.com/content/pdf/10.1007/s10489-024-05445-7.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://link.springer.com/content/pdf/10.1007/s10489-024-05445-7.pdfDirect OA link when available
- Concepts
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Computer science, Interpolation (computer graphics), Adaptive neuro fuzzy inference system, Artificial intelligence, Pattern recognition (psychology), Feature selection, Feature (linguistics), Image (mathematics), Fuzzy logic, Image scaling, Selection (genetic algorithm), Computer vision, Image processing, Fuzzy control system, Linguistics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- References (count)
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45Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W3042241076, https://openalex.org/W2914388980, https://openalex.org/W3203827541, https://openalex.org/W3188240860, https://openalex.org/W4320039173, https://openalex.org/W4310553568, https://openalex.org/W2899620715, https://openalex.org/W3056251842, https://openalex.org/W4220692384, https://openalex.org/W4311449834, https://openalex.org/W4283079051, https://openalex.org/W2055906658, https://openalex.org/W2055225600, https://openalex.org/W3118579689, https://openalex.org/W2799253018, https://openalex.org/W2019207321, https://openalex.org/W2128771953, https://openalex.org/W1963626514, https://openalex.org/W2151257102, https://openalex.org/W2047920195, https://openalex.org/W1791560514, https://openalex.org/W2121927366, https://openalex.org/W1930824406, https://openalex.org/W2141584146, https://openalex.org/W3097618751, https://openalex.org/W2132054709, https://openalex.org/W2913429812, https://openalex.org/W2151103935, https://openalex.org/W4387925137, https://openalex.org/W2111589119, https://openalex.org/W2117228865, https://openalex.org/W1677409904, https://openalex.org/W3186962463, https://openalex.org/W4224300633, https://openalex.org/W3094704314, https://openalex.org/W2079325629, https://openalex.org/W2521279577, https://openalex.org/W2109068396, https://openalex.org/W2122475393, https://openalex.org/W2962384338, https://openalex.org/W2103127765, https://openalex.org/W935139217, https://openalex.org/W2803174288, https://openalex.org/W4224030084, https://openalex.org/W4285049160 |
| referenced_works_count | 45 |
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