教學大綱與進度

課程基本資料：

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
115-1	364899	數位影像處理	1	3.0	3	★	白敦文	資工所	55	0	資工四和資工所合開

教學大綱與進度：

教師姓名	白敦文　教師諮商時間(Office Hours)
Email	twp@ntut.edu.tw
最後更新時間	2026-08-11 09:02:57
課程大綱	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.
課程進度 (1-16週)	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
彈性學習 (17-18週)	類別 ● 學生分組實作及討論(Student group practice and discussion) ● AI 輔助學習與工具應用(AI-assisted learning and tool application) 內容 Students will take time to cover all the image processing topics taught in classess. The FInal exam will be held on "2026/12/18 Friday". In the last three weeks, two weeks are holidaysalready (12/25/2026 and 01/01/2027). The last week classe (01/08/2027) will be only one class for students to propose their questions through web links. 時數 (小時) 3 學習成果 Student will try to cover the learned digital image on .Digital image fundamentals and AI applications; Image transforms;.Image enhancement; Image restoration; Color image processing; Image compression; Image segmentation and feature detection related topics. 評量比例 There is no score for the last two weeks. One week is already a holiday. (01/01/2027)
評量方式與標準	Quiz:15%, Homework:15%, Midterm 35%, and Final 35%.
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：是 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.
課程諮詢管道	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.
延伸教學與資源	● 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.
課程對應SDGs指標	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）
課程是否導入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）
備註	All lecture slides will be provided in advance through iSchool system. Lectures will be provided through MS teams.