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信号画像処理特論II_E
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| Instructor(s) |
Taizo Suzuki
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| taizo(at_no_spam)cs.tsukuba.ac.jp | |
| URL | |
| Office hours | Please contact Suzuki via email. |
| Cource# | 01CH509 |
| Area | Media Engineering |
| Basic/Advanced | |
| Course style | lecture |
| Term | SprB |
| Period | Mon 5,6 |
| Room# | 3A306 |
| Keywords | Signal processing, image processing, filtering, sparsity and energy minimization problem |
| Prerequisites |
There are no prerequisite lecture. However, it is necessary to have some understanding of high school mathematics (differential integration, matrix operations, etc.). |
| relation degree program competence | Knowledge Utilization Skills,Research Skills,Expert Knowledge |
| Goal | |
| Outline | Image processing by filtering, which is a multimedia technology, is presented. In particular, image denoising and smoothing with several mean filters, image edge extraction and sharpening with several differential filters, and similar image processing with sparsity and energy minimization problems are described. In order to understand each principle, including mathematical methods used as parts and devices that improve performance, this lecture explains from the basic concept to higher performance filtering while showing the actual processing results. |
| Course plan |
1st week: Filtering Importance of image processing, Filtering, Kind of filters 2nd week: Image Denoising and Smoothing Average filter, Median filter, Birateral filter 3rd week: Image Edge Extraction and Sharpening Differential filter, Sobel filter, Laplacian filter 4th week: Sparsity and Energy Minimization Problem Convex function, Sparsity, Total variation method 5th week: Other Image Processing Methods Contents dependent on year |
| Textbook | Not specified. Class slides will be uploaded on manaba. |
| References |
(1) Computer Vision -Expanding Element Technology and Application-, Kyoritsu Shuppan Co., Ltd. (2018). (2) Digital Image Processing [newly-revised edition], CG-ARTS Society (2015). (3) J.-L. Starck, F. Murtagh, and J. M. Fadili, Sparse Image and Signal Processing: Wavelets, Curvelets, Morphological Diversity. Cambridge University Press, (2010). (4) R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice Hall (2007). |
| Evaluation |
Grade is evaluated based on the overall score of the paper test (fill-in-the-blank + writing problems). 90 pt or more: A+ 80-89 pt: A 70-79 pt: B 60-69 pt: C 59 pt or less: D |
| TF / TA | |
| Misc. | |