Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2025 345162 Remote Sensing Image Processing 1 3.0 3 ★ Cheng-Yen Chiang ECE
太空所 7 0 　

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2025	345162	Remote Sensing Image Processing	1	3.0	3	★	Cheng-Yen Chiang	ECE 太空所	7	0

Course Plan：

Instructor Cheng-Yen Chiang　Office Hours

Email dcychiang@ntut.edu.tw

Last Updated 2024-12-19 17:33:51

Course Objective 當高解析度的數位微波影像以成趨勢後，下一世代各國之間在遙測影像的競爭上已經不再局限於光學影像中。然而無論是光學或微波影像，都是以傳統的影像處理為基礎，然後再根據彼此間的數位訊號間的差異，而有不一樣的處理方法。在國際上，越來越多實務上的應用不再只局限於傳統的數位光學影像。利用更多輔助的數位影像資料，例如數位微波影像，能獲取更高效能、更高精度的結果。本課程會以數位微波影像發展趨勢與應用介紹起，並說明影像的特性、訊號模型與處理方法，並搭配實務上的操作，達到理論與實務兼具的目的。 When high resolution digital microwave image becomes the trend, the competition of remote sensing image among countries in the next generation is no longer limited to optical image. However, both optical and microwave images are based on the traditional image processing, and then have different processing methods according to the difference between digital signals. Internationally, more and more practical applications are no longer limited to traditional digital optical imaging. The use of more complementary digital image data, such as digital microwave images, can lead to more efficient and accurate results. This course will introduce the trends and applications of digital microwave imaging, explain the characteristics of the image, signal model and processing methods, and provide practical operation to achieve both theoretical and practical purposes.

Course Schedule Week 1: Introduction: SAR development trend Week 2, 3: SAR algorithm concepts Week 4, 5, 6: Range Doppler algorithm Week 7, 8: Doppler centroid estimation Week 9: Doppler Rate Estimation Week 10, 11: RDA with high squint angle Week 12: Matching filter generation Week 13, 14, 15: Chirp scaling algorithm Week 16, 17, 18: Spectral analysis algorithm

Evaluation and grading policy Assignment and Report 60% Final report 40%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
[1] I. G. Cumming and F. H. Wong, Digital processing of synthetic aperture radar data Algorithms and Im-plementation. Boston & London: Artech house, 2005. [2] K. S. Chen, Principles of synthetic aperture radar imaging: a system simulation approach. in Signal and image processing of Earth observations series. Boca Raton London New York: CRC Press, 2016.

The access to curricular consultation 1. Email: dcychiang@ntut.edu.tw

The course corresponds to the SDGs SDG11：永續城市與社區（Sustainable Cities and Communities）
SDG13：氣候行動（Climate Action）

Note
　

Instructor	Cheng-Yen Chiang　Office Hours
Email	dcychiang@ntut.edu.tw
Last Updated	2024-12-19 17:33:51
Course Objective	當高解析度的數位微波影像以成趨勢後，下一世代各國之間在遙測影像的競爭上已經不再局限於光學影像中。然而無論是光學或微波影像，都是以傳統的影像處理為基礎，然後再根據彼此間的數位訊號間的差異，而有不一樣的處理方法。在國際上，越來越多實務上的應用不再只局限於傳統的數位光學影像。利用更多輔助的數位影像資料，例如數位微波影像，能獲取更高效能、更高精度的結果。本課程會以數位微波影像發展趨勢與應用介紹起，並說明影像的特性、訊號模型與處理方法，並搭配實務上的操作，達到理論與實務兼具的目的。 When high resolution digital microwave image becomes the trend, the competition of remote sensing image among countries in the next generation is no longer limited to optical image. However, both optical and microwave images are based on the traditional image processing, and then have different processing methods according to the difference between digital signals. Internationally, more and more practical applications are no longer limited to traditional digital optical imaging. The use of more complementary digital image data, such as digital microwave images, can lead to more efficient and accurate results. This course will introduce the trends and applications of digital microwave imaging, explain the characteristics of the image, signal model and processing methods, and provide practical operation to achieve both theoretical and practical purposes.
Course Schedule	Week 1: Introduction: SAR development trend Week 2, 3: SAR algorithm concepts Week 4, 5, 6: Range Doppler algorithm Week 7, 8: Doppler centroid estimation Week 9: Doppler Rate Estimation Week 10, 11: RDA with high squint angle Week 12: Matching filter generation Week 13, 14, 15: Chirp scaling algorithm Week 16, 17, 18: Spectral analysis algorithm
Evaluation and grading policy	Assignment and Report 60% Final report 40%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes [1] I. G. Cumming and F. H. Wong, Digital processing of synthetic aperture radar data Algorithms and Im-plementation. Boston & London: Artech house, 2005. [2] K. S. Chen, Principles of synthetic aperture radar imaging: a system simulation approach. in Signal and image processing of Earth observations series. Boca Raton London New York: CRC Press, 2016.
The access to curricular consultation	1. Email: dcychiang@ntut.edu.tw
The course corresponds to the SDGs	SDG11：永續城市與社區（Sustainable Cities and Communities） SDG13：氣候行動（Climate Action）
Note