Speckle Noise Reduction Method Based on Fuzzy Approach for Synthetic Aperture Radar Images
Synthetic Aperture Radars (SAR) are classified as active sensors. It has been capable of producing images with high spatial resolution, and able to observe at day and night and in all-weather condition. With these advantages, SAR image becomes more popular than the Optical image. SAR image formatio...
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2016
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my.ump.umpir.159032020-02-21T07:54:56Z http://umpir.ump.edu.my/id/eprint/15903/ Speckle Noise Reduction Method Based on Fuzzy Approach for Synthetic Aperture Radar Images Santoso, Ardhi W. Bayuaji, Luhur Jasni, Mohamad Zain Pebrianti, Dwi Lim, Tien Sze Habibah, Lateh TK Electrical engineering. Electronics Nuclear engineering Synthetic Aperture Radars (SAR) are classified as active sensors. It has been capable of producing images with high spatial resolution, and able to observe at day and night and in all-weather condition. With these advantages, SAR image becomes more popular than the Optical image. SAR image formation process led to speckle noise; it causes difficulties in the process of interpretation and analysis of SAR images. Fuzzy approach is a technique that can be used to reduce speckle noise. It has been used in the ultrasonic image in the medical field and showed good performance in image filtering to reduce speckle noise. Implemented to SAR images for reduce speckle noise by replacing the center pixel local neighbor Frost's with digital numbers that calculate by fuzzy filter. Proposed filters applied into a homogeneous and heterogeneous area in SAR images, aims to measure the robustness of the proposed filters in speckle noise reduction and texture preservation, mainly in homogeneous areas. All of areas is filtered using proposed filters; that's, Frost-TMED, Frost-ATMED, Frost-ATMAV and Frost-TMAV combination. Evaluation has been made, to measure the performance of filters, major in speckle noise reduction and texture preservation. The experiment result shows that the combination of Frost-TMAV has the highest performance. It has been verified that the Frost-TMAV filtering approach is performing better than the other filters, which mean being able to produce good-quality images than other filters. It also produces an obvious example of speckle reduction processing; features of tissues are enhanced and a good preserve on texture. The result shows that fuzzy approach has robustness to reduce speckle noise in SAR image, especially in ALOS-PALSAR’s raw data, which require clarity of the image for further processing. Universiti Malaysia Pahang 2016 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/15903/1/P036%20pg243-252.pdf Santoso, Ardhi W. and Bayuaji, Luhur and Jasni, Mohamad Zain and Pebrianti, Dwi and Lim, Tien Sze and Habibah, Lateh (2016) Speckle Noise Reduction Method Based on Fuzzy Approach for Synthetic Aperture Radar Images. In: Proceedings of The National Conference for Postgraduate Research (NCON-PGR 2016), 24-25 September 2016 , Universiti Malaysia Pahang (UMP), Pekan, Pahang. pp. 243-252.. http://ee.ump.edu.my/ncon/wp-content/uploads/2016/10/Proceeding-NCON-PGR-2016.zip |
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TK Electrical engineering. Electronics Nuclear engineering Santoso, Ardhi W. Bayuaji, Luhur Jasni, Mohamad Zain Pebrianti, Dwi Lim, Tien Sze Habibah, Lateh Speckle Noise Reduction Method Based on Fuzzy Approach for Synthetic Aperture Radar Images |
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Synthetic Aperture Radars (SAR) are classified as active sensors. It has been capable of producing images with
high spatial resolution, and able to observe at day and night and in all-weather condition. With these advantages, SAR image becomes more popular than the Optical image. SAR image formation process led to speckle noise; it causes difficulties in the
process of interpretation and analysis of SAR images. Fuzzy approach is a technique that can be used to reduce speckle noise. It has been used in the ultrasonic image in the medical field and showed good performance in image filtering to reduce speckle
noise. Implemented to SAR images for reduce speckle noise by replacing the center pixel local neighbor Frost's with digital numbers that calculate by fuzzy filter. Proposed filters applied into a homogeneous and heterogeneous area in SAR images,
aims to measure the robustness of the proposed filters in speckle noise reduction and texture preservation, mainly in homogeneous areas. All of areas is filtered using proposed filters; that's, Frost-TMED, Frost-ATMED, Frost-ATMAV and Frost-TMAV combination. Evaluation has been made, to measure the performance of filters, major in speckle noise reduction
and texture preservation. The experiment result shows that the combination of Frost-TMAV has the highest performance. It has
been verified that the Frost-TMAV filtering approach is performing better than the other filters, which mean being able to
produce good-quality images than other filters. It also produces an obvious example of speckle reduction processing; features
of tissues are enhanced and a good preserve on texture. The result shows that fuzzy approach has robustness to reduce speckle noise in SAR image, especially in ALOS-PALSAR’s raw data, which require clarity of the image for further processing. |
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Conference or Workshop Item |
author |
Santoso, Ardhi W. Bayuaji, Luhur Jasni, Mohamad Zain Pebrianti, Dwi Lim, Tien Sze Habibah, Lateh |
author_facet |
Santoso, Ardhi W. Bayuaji, Luhur Jasni, Mohamad Zain Pebrianti, Dwi Lim, Tien Sze Habibah, Lateh |
author_sort |
Santoso, Ardhi W. |
title |
Speckle Noise Reduction Method Based on Fuzzy Approach for Synthetic Aperture Radar Images |
title_short |
Speckle Noise Reduction Method Based on Fuzzy Approach for Synthetic Aperture Radar Images |
title_full |
Speckle Noise Reduction Method Based on Fuzzy Approach for Synthetic Aperture Radar Images |
title_fullStr |
Speckle Noise Reduction Method Based on Fuzzy Approach for Synthetic Aperture Radar Images |
title_full_unstemmed |
Speckle Noise Reduction Method Based on Fuzzy Approach for Synthetic Aperture Radar Images |
title_sort |
speckle noise reduction method based on fuzzy approach for synthetic aperture radar images |
publisher |
Universiti Malaysia Pahang |
publishDate |
2016 |
url |
http://umpir.ump.edu.my/id/eprint/15903/1/P036%20pg243-252.pdf http://umpir.ump.edu.my/id/eprint/15903/ http://ee.ump.edu.my/ncon/wp-content/uploads/2016/10/Proceeding-NCON-PGR-2016.zip |
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13.211869 |