User Manual for Model-based Imaging Inverse Problem
Fuente:
arXiv
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| Auteur principal: | |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866914016980369408 |
|---|---|
| author | Wang, Xiaodong |
| author_facet | Wang, Xiaodong |
| contents | This user manual is intended to provide a detailed description on model-based optimization for imaging inverse problem. Theseproblems can be particularly complex and challenging, especially for individuals without prior exposure to convex optimization orinverse problem theory, like myself. In light of this, I am writing this manual to clarify and systematically organize the mathematicalrationale underlying imaging inverse problems. This manual might not be accurate in mathmatical notion but more focus on the logicalthinking on how to solve and proceed to solve the problems. If you want to think deep about something, try to raise questions! Thismanual is seaprated into four sections, aiming to answer the following four questions: (1) What is inverse imaging problem? (2) Why optimization is used to solve the inverse imaging problem? (3) How to solve the optimization problem? (4) How to implement the optimization algorithm in real imaging system? |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_01572 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | User Manual for Model-based Imaging Inverse Problem Wang, Xiaodong Numerical Analysis Computer Vision and Pattern Recognition This user manual is intended to provide a detailed description on model-based optimization for imaging inverse problem. Theseproblems can be particularly complex and challenging, especially for individuals without prior exposure to convex optimization orinverse problem theory, like myself. In light of this, I am writing this manual to clarify and systematically organize the mathematicalrationale underlying imaging inverse problems. This manual might not be accurate in mathmatical notion but more focus on the logicalthinking on how to solve and proceed to solve the problems. If you want to think deep about something, try to raise questions! Thismanual is seaprated into four sections, aiming to answer the following four questions: (1) What is inverse imaging problem? (2) Why optimization is used to solve the inverse imaging problem? (3) How to solve the optimization problem? (4) How to implement the optimization algorithm in real imaging system? |
| title | User Manual for Model-based Imaging Inverse Problem |
| topic | Numerical Analysis Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2509.01572 |