Course Syllabus

Course Information：

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

Fall Semester
Year 2026 364899 Digital Image Processing 1 3.0 3 ★ Tun-Wen Pai GCSIE 4 0 資工四和資工所合開

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2026	364899	Digital Image Processing	1	3.0	3	★	Tun-Wen Pai	GCSIE	4	0	資工四和資工所合開

Course Plan：

Instructor Tun-Wen Pai　Office Hours

Email twp@ntut.edu.tw

Last Updated 2026-06-03 13:21:47

Course Objective This course will be lectured in Chinese/English. Teaching contents include the following topics: 1.Digital image fundamentals and 2.Image transforms. 3.Image enhancement 4. Image restoration 5. Color image processing. 6. Image compression. 7. Image segmentation and feature detection 8. Representation and description 9. Recognition and interpretation 10. Applications: ALV navigation and medical image.

Course Schedule 1. Introduce to Image Processing AI applications Computer Imaging Systems Human Visual Perception Image Representation 2. Introduction to Image Analysis Preprocessing Techniques Edge/Line Detection Image Segmentation Discrete Transform Feature Extraction 3. Image Enhancement in Spatial Domain Grayscale Modification Image Sharpening Filters Image Smoothing Filters 4. Image Enhancement in Frequency Domain Fourier Transform Image Sharpening Filters Image Smoothing Filters Homomorphic Filtering 5. Introduction to Image Restoration Spatial Filters for Noise Removal Frequency Filters for Noise Removal 6. Color Image Processing Color Models Pseudo-color Image Processing Color Transformation 7. Compression Algorithms Image Compression Models Different Compression Algorithms

Evaluation and grading policy Quiz:15%, Homework:15%, Midterm 30%, and Final 30%, Final paper report 10%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
Textbook： Digital Image Processing Authors：Rafael C. Gonzalez & Richard E. Woods (開發圖書公司) 4th Edition References： Digital Image Processing Using MATLAB by Rafael C. Gonzalez, Richard E. Woods, and Steven L. Eddins, 2nd Edition

The access to curricular consultation 研究室分機(Extension): 4222
位置(Office): 宏裕科技大樓1524 (Hung-Yu Research Tech. Building)
Office hours: Wed. 1600-18:00

Any linking problem related to MS teams, please contact TA individually.

Expanding teaching and resources ● 混成學習 (Blended Learning)
課程結合實體授課與線上學習（同步視訊／非同步活動）。
Combines face-to-face instruction with online learning (including synchronous video sessions or asynchronous activities).
● 數位教材資源應用 (Application of Digital Resources)
採用影音多媒體或具開放授權之資源（如OCW、開放教科書）作為主要或輔助教材。
Adopts multimedia or open-licensed resources (e.g., OCW, Open Textbooks) as primary or supplementary teaching materials.
● 數位科技融入 (Digital Technology Integration)
運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。
Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.

The course corresponds to the SDGs SDG4：優質教育（Quality Education）
SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure）
SDG11：永續城市與社區（Sustainable Cities and Communities）

Does the course incorporate AI ● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process）
● 使用生成式AI進行課堂即時互動（Use generative AI for real-time classroom interaction）
● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI）

Note
All lecture slides will be provided in advance through iSchool system.
Lectures will be provided through MS teams.

Instructor	Tun-Wen Pai　Office Hours
Email	twp@ntut.edu.tw
Last Updated	2026-06-03 13:21:47
Course Objective	This course will be lectured in Chinese/English. Teaching contents include the following topics: 1.Digital image fundamentals and 2.Image transforms. 3.Image enhancement 4. Image restoration 5. Color image processing. 6. Image compression. 7. Image segmentation and feature detection 8. Representation and description 9. Recognition and interpretation 10. Applications: ALV navigation and medical image.
Course Schedule	1. Introduce to Image Processing AI applications Computer Imaging Systems Human Visual Perception Image Representation 2. Introduction to Image Analysis Preprocessing Techniques Edge/Line Detection Image Segmentation Discrete Transform Feature Extraction 3. Image Enhancement in Spatial Domain Grayscale Modification Image Sharpening Filters Image Smoothing Filters 4. Image Enhancement in Frequency Domain Fourier Transform Image Sharpening Filters Image Smoothing Filters Homomorphic Filtering 5. Introduction to Image Restoration Spatial Filters for Noise Removal Frequency Filters for Noise Removal 6. Color Image Processing Color Models Pseudo-color Image Processing Color Transformation 7. Compression Algorithms Image Compression Models Different Compression Algorithms
Evaluation and grading policy	Quiz:15%, Homework:15%, Midterm 30%, and Final 30%, Final paper report 10%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Textbook： Digital Image Processing Authors：Rafael C. Gonzalez & Richard E. Woods (開發圖書公司) 4th Edition References： Digital Image Processing Using MATLAB by Rafael C. Gonzalez, Richard E. Woods, and Steven L. Eddins, 2nd Edition
The access to curricular consultation	研究室分機(Extension): 4222 位置(Office): 宏裕科技大樓1524 (Hung-Yu Research Tech. Building) Office hours: Wed. 1600-18:00 Any linking problem related to MS teams, please contact TA individually.
Expanding teaching and resources	● 混成學習 (Blended Learning) 課程結合實體授課與線上學習（同步視訊／非同步活動）。 Combines face-to-face instruction with online learning (including synchronous video sessions or asynchronous activities). ● 數位教材資源應用 (Application of Digital Resources) 採用影音多媒體或具開放授權之資源（如OCW、開放教科書）作為主要或輔助教材。 Adopts multimedia or open-licensed resources (e.g., OCW, Open Textbooks) as primary or supplementary teaching materials. ● 數位科技融入 (Digital Technology Integration) 運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。 Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.
The course corresponds to the SDGs	SDG4：優質教育（Quality Education） SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure） SDG11：永續城市與社區（Sustainable Cities and Communities）
Does the course incorporate AI	● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process） ● 使用生成式AI進行課堂即時互動（Use generative AI for real-time classroom interaction） ● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI）
Note	All lecture slides will be provided in advance through iSchool system. Lectures will be provided through MS teams.