The Bright Feature Transform for Prominent Point Scatterer Detection and Tone Mapping
Detecting bright point scatterers plays an important role in assessing the quality of many sonar, radar, and medical ultrasound imaging systems, especially for characterizing the resolution. Traditionally, prominent scatterers, also known as coherent scatterers, are usually detected by employing thr...
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MDPI AG
2025-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/6/1037 |
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| author | Gregory D. Vetaw Suren Jayasuriya |
| author_facet | Gregory D. Vetaw Suren Jayasuriya |
| author_sort | Gregory D. Vetaw |
| collection | DOAJ |
| description | Detecting bright point scatterers plays an important role in assessing the quality of many sonar, radar, and medical ultrasound imaging systems, especially for characterizing the resolution. Traditionally, prominent scatterers, also known as coherent scatterers, are usually detected by employing thresholding techniques alongside statistical measures in the detection processing chain. However, these methods can perform poorly in detecting point-like scatterers in relatively high levels of speckle background and can distort the structure of the scatterer when visualized. This paper introduces a fast image-processing method to visually identify and detect point scatterers in synthetic aperture imagery using the bright feature transform (BFT). The BFT is analytic, computationally inexpensive, and requires no thresholding or parameter tuning. We derive this method by analyzing an ideal point scatterer’s response with respect to pixel intensity and contrast around neighboring pixels and non-adjacent pixels. We show that this method preserves the general structure and the width of the bright scatterer while performing tone mapping, which can then be used for downstream image characterization and analysis. We then modify the BFT to present a difference of trigonometric functions to mitigate speckle scatterers and other random noise sources found in the imagery. We evaluate the performance of our methods on simulated and real synthetic aperture sonar and radar images, and show qualitative results on how the methods perform tone mapping on reconstructed input imagery in such a way to highlight the bright scatterer, which is insensitive to seafloor textures and high speckle noise levels. |
| format | Article |
| id | doaj-art-aebe949a10ae46bb8571d1e41f42e8b7 |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-aebe949a10ae46bb8571d1e41f42e8b72025-08-20T01:48:54ZengMDPI AGRemote Sensing2072-42922025-03-01176103710.3390/rs17061037The Bright Feature Transform for Prominent Point Scatterer Detection and Tone MappingGregory D. Vetaw0Suren Jayasuriya1The School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85281, USAThe School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85281, USADetecting bright point scatterers plays an important role in assessing the quality of many sonar, radar, and medical ultrasound imaging systems, especially for characterizing the resolution. Traditionally, prominent scatterers, also known as coherent scatterers, are usually detected by employing thresholding techniques alongside statistical measures in the detection processing chain. However, these methods can perform poorly in detecting point-like scatterers in relatively high levels of speckle background and can distort the structure of the scatterer when visualized. This paper introduces a fast image-processing method to visually identify and detect point scatterers in synthetic aperture imagery using the bright feature transform (BFT). The BFT is analytic, computationally inexpensive, and requires no thresholding or parameter tuning. We derive this method by analyzing an ideal point scatterer’s response with respect to pixel intensity and contrast around neighboring pixels and non-adjacent pixels. We show that this method preserves the general structure and the width of the bright scatterer while performing tone mapping, which can then be used for downstream image characterization and analysis. We then modify the BFT to present a difference of trigonometric functions to mitigate speckle scatterers and other random noise sources found in the imagery. We evaluate the performance of our methods on simulated and real synthetic aperture sonar and radar images, and show qualitative results on how the methods perform tone mapping on reconstructed input imagery in such a way to highlight the bright scatterer, which is insensitive to seafloor textures and high speckle noise levels.https://www.mdpi.com/2072-4292/17/6/1037point scatterersynthetic aperture radarsynthetic aperture sonar |
| spellingShingle | Gregory D. Vetaw Suren Jayasuriya The Bright Feature Transform for Prominent Point Scatterer Detection and Tone Mapping Remote Sensing point scatterer synthetic aperture radar synthetic aperture sonar |
| title | The Bright Feature Transform for Prominent Point Scatterer Detection and Tone Mapping |
| title_full | The Bright Feature Transform for Prominent Point Scatterer Detection and Tone Mapping |
| title_fullStr | The Bright Feature Transform for Prominent Point Scatterer Detection and Tone Mapping |
| title_full_unstemmed | The Bright Feature Transform for Prominent Point Scatterer Detection and Tone Mapping |
| title_short | The Bright Feature Transform for Prominent Point Scatterer Detection and Tone Mapping |
| title_sort | bright feature transform for prominent point scatterer detection and tone mapping |
| topic | point scatterer synthetic aperture radar synthetic aperture sonar |
| url | https://www.mdpi.com/2072-4292/17/6/1037 |
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