Perceptual image processing algorithm benchmarking
Since the Human Visual System (HVS) is the ultimate receiver and appreciator of natural scenes, many visual attention models have been developed and applied to various image processing applications in the past decade.In order to provide the insight for effective deployment in this project, we study...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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2012
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| Online Access: | http://hdl.handle.net/10356/48452 |
| _version_ | 1811677001217474560 |
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| author | Nur Shabrina Rusli. |
| author2 | Lin Weisi |
| author_facet | Lin Weisi Nur Shabrina Rusli. |
| author_sort | Nur Shabrina Rusli. |
| collection | NTU |
| description | Since the Human Visual System (HVS) is the ultimate receiver and appreciator of natural scenes, many visual attention models have been developed and applied to various image processing applications in the past decade.In order to provide the insight for effective deployment in this project, we study various existing saliency detection models and different image processing techniques. The performance of the respective experiments is analyzed. Benchmarking the state-of-the-art technology is then made in the related area. |
| first_indexed | 2024-10-01T02:30:25Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/48452 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:30:25Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | ntu-10356/484522023-03-03T20:34:19Z Perceptual image processing algorithm benchmarking Nur Shabrina Rusli. Lin Weisi School of Computer Engineering Centre for Multimedia and Network Technology DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Since the Human Visual System (HVS) is the ultimate receiver and appreciator of natural scenes, many visual attention models have been developed and applied to various image processing applications in the past decade.In order to provide the insight for effective deployment in this project, we study various existing saliency detection models and different image processing techniques. The performance of the respective experiments is analyzed. Benchmarking the state-of-the-art technology is then made in the related area. Bachelor of Engineering (Computer Engineering) 2012-04-24T03:18:05Z 2012-04-24T03:18:05Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/48452 en Nanyang Technological University 54 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Nur Shabrina Rusli. Perceptual image processing algorithm benchmarking |
| title | Perceptual image processing algorithm benchmarking |
| title_full | Perceptual image processing algorithm benchmarking |
| title_fullStr | Perceptual image processing algorithm benchmarking |
| title_full_unstemmed | Perceptual image processing algorithm benchmarking |
| title_short | Perceptual image processing algorithm benchmarking |
| title_sort | perceptual image processing algorithm benchmarking |
| topic | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision |
| url | http://hdl.handle.net/10356/48452 |
| work_keys_str_mv | AT nurshabrinarusli perceptualimageprocessingalgorithmbenchmarking |