Low light image enhancement using curvelet transform and iterative back projection
Abstract With the advancement of technology in image capturing, people are accustomed to high-resolution images. One of the primary necessities of an image capturing system is to provide the same. However, in many cases, the image resolution may not be reaching the expectations of the user which lea...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-27838-3 |
| _version_ | 1797945890886909952 |
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| author | Sreekala Kannoth Sateesh Kumar H. C. Raja K. B. |
| author_facet | Sreekala Kannoth Sateesh Kumar H. C. Raja K. B. |
| author_sort | Sreekala Kannoth |
| collection | DOAJ |
| description | Abstract With the advancement of technology in image capturing, people are accustomed to high-resolution images. One of the primary necessities of an image capturing system is to provide the same. However, in many cases, the image resolution may not be reaching the expectations of the user which leads to a decrease in user experience. This is a common phenomenon that occurs when the images are captured in low light or if the image encounters a distortion either because of lack of exposure or the image capturing devices may be equipped with a small size sensor. In this work, a resolution enhancement technique using the concepts of curvelet transform and iterative back projection is presented. Sparse representation of images can be enhanced using a combination of curvelet transforms with iterative back projection. Application of curvelet transform along with iterative back projection algorithm on low light images results in enhancing the resolution of the images. The resultant images from here then passed through the inverse transform block and gives an image with contrast enhancement which leads to the user experience improvement. The antiquated image enhancement with improvement in the resolution is validated with the measurement of peak signal-to-noise ratio and structural similarity index. The usage of curvelet transform with iterative back projection leads to the restoration of the image resolution by minimizing the distortions, thus leading to an enhanced image whose edge details are retained. |
| first_indexed | 2024-04-10T21:02:18Z |
| format | Article |
| id | doaj.art-9a3cba00f6ac493a81885e144411215a |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-10T21:02:18Z |
| publishDate | 2023-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-9a3cba00f6ac493a81885e144411215a2023-01-22T12:14:40ZengNature PortfolioScientific Reports2045-23222023-01-0113111010.1038/s41598-023-27838-3Low light image enhancement using curvelet transform and iterative back projectionSreekala Kannoth0Sateesh Kumar H. C.1Raja K. B.2Visvesvaraya Technological UniversityDepartment of ECE, Sapthagiri College of Engineering BengaluruDepartment of ECE, University Visvesvaraya College of EngineeringAbstract With the advancement of technology in image capturing, people are accustomed to high-resolution images. One of the primary necessities of an image capturing system is to provide the same. However, in many cases, the image resolution may not be reaching the expectations of the user which leads to a decrease in user experience. This is a common phenomenon that occurs when the images are captured in low light or if the image encounters a distortion either because of lack of exposure or the image capturing devices may be equipped with a small size sensor. In this work, a resolution enhancement technique using the concepts of curvelet transform and iterative back projection is presented. Sparse representation of images can be enhanced using a combination of curvelet transforms with iterative back projection. Application of curvelet transform along with iterative back projection algorithm on low light images results in enhancing the resolution of the images. The resultant images from here then passed through the inverse transform block and gives an image with contrast enhancement which leads to the user experience improvement. The antiquated image enhancement with improvement in the resolution is validated with the measurement of peak signal-to-noise ratio and structural similarity index. The usage of curvelet transform with iterative back projection leads to the restoration of the image resolution by minimizing the distortions, thus leading to an enhanced image whose edge details are retained.https://doi.org/10.1038/s41598-023-27838-3 |
| spellingShingle | Sreekala Kannoth Sateesh Kumar H. C. Raja K. B. Low light image enhancement using curvelet transform and iterative back projection Scientific Reports |
| title | Low light image enhancement using curvelet transform and iterative back projection |
| title_full | Low light image enhancement using curvelet transform and iterative back projection |
| title_fullStr | Low light image enhancement using curvelet transform and iterative back projection |
| title_full_unstemmed | Low light image enhancement using curvelet transform and iterative back projection |
| title_short | Low light image enhancement using curvelet transform and iterative back projection |
| title_sort | low light image enhancement using curvelet transform and iterative back projection |
| url | https://doi.org/10.1038/s41598-023-27838-3 |
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