AWGN Removal Using Modified Steering Kernel and Image Matching
Image noise occurs during acquisition and transmission and adversely affects processes, such as image segmentation and object recognition and classification. Various techniques are being studied for noise removal, and with the recent development of hardware and image processing algorithms, noise rem...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/22/11588 |
| _version_ | 1797466007167565824 |
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| author | Bong-Won Cheon Nam-Ho Kim |
| author_facet | Bong-Won Cheon Nam-Ho Kim |
| author_sort | Bong-Won Cheon |
| collection | DOAJ |
| description | Image noise occurs during acquisition and transmission and adversely affects processes, such as image segmentation and object recognition and classification. Various techniques are being studied for noise removal, and with the recent development of hardware and image processing algorithms, noise removal techniques that combine non-local techniques are attracting attention. However, one disadvantage of this method is that blurring occurs in the edges and boundary line of the resulting image. In this study, we proposed a modified local steering kernel based on image matching to improve these shortcomings. The proposed technique uses image matching to differentiate the weight obtained by the steering kernel according to the local characteristics of the image and calculates the weight of the filter based on the similarity between the center window and the matching window. The resulting images were quantitatively evaluation and enlargement of images were used and compared with the existing noise removal algorithms. The proposed algorithm showed clearer contrast in the enlarged images and better results than the conventional image restoration techniques in the quantitative evaluation using peak signal-to-noise ratio and structural similarity index. |
| first_indexed | 2024-03-09T18:29:42Z |
| format | Article |
| id | doaj.art-c873023f6bca47f181169eec3154dcc9 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T18:29:42Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-c873023f6bca47f181169eec3154dcc92023-11-24T07:37:40ZengMDPI AGApplied Sciences2076-34172022-11-0112221158810.3390/app122211588AWGN Removal Using Modified Steering Kernel and Image MatchingBong-Won Cheon0Nam-Ho Kim1Department of Intelligent Robot Engineering, Pukyong National University, Busan 48513, Republic of KoreaSchool of Electrical Engineering, Pukyong National University, Busan 48513, Republic of KoreaImage noise occurs during acquisition and transmission and adversely affects processes, such as image segmentation and object recognition and classification. Various techniques are being studied for noise removal, and with the recent development of hardware and image processing algorithms, noise removal techniques that combine non-local techniques are attracting attention. However, one disadvantage of this method is that blurring occurs in the edges and boundary line of the resulting image. In this study, we proposed a modified local steering kernel based on image matching to improve these shortcomings. The proposed technique uses image matching to differentiate the weight obtained by the steering kernel according to the local characteristics of the image and calculates the weight of the filter based on the similarity between the center window and the matching window. The resulting images were quantitatively evaluation and enlargement of images were used and compared with the existing noise removal algorithms. The proposed algorithm showed clearer contrast in the enlarged images and better results than the conventional image restoration techniques in the quantitative evaluation using peak signal-to-noise ratio and structural similarity index.https://www.mdpi.com/2076-3417/12/22/11588AWGNmodified steering kernelnoise removalimage matching |
| spellingShingle | Bong-Won Cheon Nam-Ho Kim AWGN Removal Using Modified Steering Kernel and Image Matching Applied Sciences AWGN modified steering kernel noise removal image matching |
| title | AWGN Removal Using Modified Steering Kernel and Image Matching |
| title_full | AWGN Removal Using Modified Steering Kernel and Image Matching |
| title_fullStr | AWGN Removal Using Modified Steering Kernel and Image Matching |
| title_full_unstemmed | AWGN Removal Using Modified Steering Kernel and Image Matching |
| title_short | AWGN Removal Using Modified Steering Kernel and Image Matching |
| title_sort | awgn removal using modified steering kernel and image matching |
| topic | AWGN modified steering kernel noise removal image matching |
| url | https://www.mdpi.com/2076-3417/12/22/11588 |
| work_keys_str_mv | AT bongwoncheon awgnremovalusingmodifiedsteeringkernelandimagematching AT namhokim awgnremovalusingmodifiedsteeringkernelandimagematching |