Gaussian noise level estimation in SVD domain for images
Accurate estimation of noise level is of fundamental interest in a wide variety of vision and image processing applications as it is critical to the processing techniques that follow. In this paper, a new, effective noise level estimation method is proposed based on the study of singular values of n...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Online Access: | https://hdl.handle.net/10356/84310 http://hdl.handle.net/10220/13015 |
| _version_ | 1826127073903640576 |
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| author | Lin, Weisi Liu, Wei. |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Lin, Weisi Liu, Wei. |
| author_sort | Lin, Weisi |
| collection | NTU |
| description | Accurate estimation of noise level is of fundamental interest in a wide variety of vision and image processing applications as it is critical to the processing techniques that follow. In this paper, a new, effective noise level estimation method is proposed based on the study of singular values of noise-corrupted images. There are two major novel aspects of this work to address the major challenges in noise estimation: 1) the use of the tail of singular values for noise estimation to alleviate the influence of the signal on the data basis for the noise estimation process, 2) the addition of known noise to estimate the content-dependent parameter, so that the proposed scheme is adaptive to visual signal and therefore it enables wider application scope of the proposed scheme. The analysis and experiments results demonstrate that the proposed algorithm can reliably infer noise levels and show robust behavior over a wide range of visual content and noise conditions, in comparison with the relevant existing methods. |
| first_indexed | 2024-10-01T07:02:49Z |
| format | Conference Paper |
| id | ntu-10356/84310 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:02:49Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/843102020-05-28T07:17:47Z Gaussian noise level estimation in SVD domain for images Lin, Weisi Liu, Wei. School of Computer Engineering IEEE International Conference on Multimedia and Expo (2012 : Melbourne, Australia) DRNTU::Engineering::Computer science and engineering Accurate estimation of noise level is of fundamental interest in a wide variety of vision and image processing applications as it is critical to the processing techniques that follow. In this paper, a new, effective noise level estimation method is proposed based on the study of singular values of noise-corrupted images. There are two major novel aspects of this work to address the major challenges in noise estimation: 1) the use of the tail of singular values for noise estimation to alleviate the influence of the signal on the data basis for the noise estimation process, 2) the addition of known noise to estimate the content-dependent parameter, so that the proposed scheme is adaptive to visual signal and therefore it enables wider application scope of the proposed scheme. The analysis and experiments results demonstrate that the proposed algorithm can reliably infer noise levels and show robust behavior over a wide range of visual content and noise conditions, in comparison with the relevant existing methods. 2013-08-05T06:49:10Z 2019-12-06T15:42:33Z 2013-08-05T06:49:10Z 2019-12-06T15:42:33Z 2012 2012 Conference Paper https://hdl.handle.net/10356/84310 http://hdl.handle.net/10220/13015 10.1109/ICME.2012.27 en |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Lin, Weisi Liu, Wei. Gaussian noise level estimation in SVD domain for images |
| title | Gaussian noise level estimation in SVD domain for images |
| title_full | Gaussian noise level estimation in SVD domain for images |
| title_fullStr | Gaussian noise level estimation in SVD domain for images |
| title_full_unstemmed | Gaussian noise level estimation in SVD domain for images |
| title_short | Gaussian noise level estimation in SVD domain for images |
| title_sort | gaussian noise level estimation in svd domain for images |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/84310 http://hdl.handle.net/10220/13015 |
| work_keys_str_mv | AT linweisi gaussiannoiselevelestimationinsvddomainforimages AT liuwei gaussiannoiselevelestimationinsvddomainforimages |