Course title
L00190002
Digital Media Processing

IJIRI Takashi
Middle-level Diploma Policy (mDP)
Program / Major mDP Goals Courses
Fundamental Mechanical Engineering F 産業界や社会の要請を把握して解決するべき課題を設定し、さまざまな工学分野の知識を関連付けながら設計生産技術を活用することで、立案した構想に従って研究を進め課題を解決することができる。 Sub
Advanced Mechanical Engineering F 産業界や社会の要請を把握して解決するべき課題を設定し、機械工学の学理を応用して異分野を含む融合分野で革新的な機能を創成することができる。 Sub
Environment and Materials Engineering B 地球環境や地域社会との調和を見据えて、さまざまな工学分野に関わる問題を解決することができる。 Sub
Chemistry and Biotechnology B 地球環境や地域社会との調和を見据えて、さまざまな工学分野に関わる問題を解決することができる。 Sub
Electrical Engineering and Robotics D 電気工学や関連する工学の技術分野を課題に適用し、社会の要求を解決するために応用することができる。 Sub
Advanced Electronic Engineering E 専門的デザイン課題について解決する能力を身に付けることができる。 Sub
Information and Communications Engineering F 社会のニーズに対して技術課題を主体的に発見し、工学分野における分野横断的な知識も活用しつつ、計画的・継続的に取り組んで課題を達成することができる。 Sub
Computer Science and Engineering B-2 コンピュータサイエンスの各分野の基礎知識とその応用能力を身に付けることができる。 Main
Urban Infrastructure and Environment G ⼟⽊⼯学における現実の問題について、⼯学・専⾨基礎知識を⽤いて理解・解決することができる。 Sub
Purpose of class
To learn various basic algorithms for image processing, including convolution filtering, Fourier transform, affine transform, deconvolution. To improving programing skills through python programing exercises for image processing.
Course description
Image processing is indispensable for various fields, including industry, natural science, and entertainment. This class, Digital Media Processing, introduces basic image-processing techniques such as digital image acquisition, filtering, and geometric transform. For most of algorithms presented in class, interactive demonstrations with source codes (python) will be provided to support your deep comprehension.
Goals and objectives
  1. Introduction to digital image processing - Goal is that students understand various techniques of image acquisition and can explain them.
  2. Image filtering - Goal is that students understand basic filtering techniques, such as tone curve, linear and non-linear filters and can explain them.
  3. Geometric transformation – Goal is that students understand affine transform and interpolation and can explain them.
  4. Image compression – Goal is that students understand and explain basic information theory and image compression algorithms.
  5. Programing assignments - Goal is that students write programs of various basic image processing algorithms in python.
Relationship between 'Goals and Objectives' and 'Course Outcomes'

programing assignment mini exams exam Total.
1. 0% 5% 10% 15%
2. 0% 5% 10% 15%
3. 0% 5% 10% 15%
4. 0% 5% 10% 15%
5. 40% 40%
Total. 40% 20% 40% -
Evaluation method and criteria
By mini exams (20%), exam (40) and assignments (40%).
-- The mini exam and exam will contain basic questions (30~40%), developmental questions (20~30%), and calculation (30~40%) with respect to image processing.
-- Programming assignments contain basic assignments (60%) and developmental assignments (40%) with respect to image processing and image recognition.

If solving all basic questions and programming assignments, it will be evaluated as 60%.
Language
Japanese
Class schedule

Class schedule HW assignments (Including preparation and review of the class.) Amount of Time Required
1. Introduction 1: Digital image, sampling and quantization
# mini exam
Preparation and review the lecture by using online lecture notes. 200minutes
2. Introduction 2: Digital camera, human vision, color
# mini exam
Preparation and review the lecture by using online lecture notes. 200minutes
3. Filtering 1: tone curve, linear filters
# mini exam
Preparation and review the lecture by using online lecture notes. 200minutes
4. Filtering 2: non-linear filters, halftoning
# mini exam
Preparation and review the lecture by using online lecture notes. 200minutes
5. Filtering 3: DFT, frequency filters
# mini exam
Preparation and review the lecture by using online lecture notes. 200minutes
6. Geometric transform : affine transform and image interpolation
# mini exam
Preparation and review the lecture by using online lecture notes. 200minutes
7. Convolution and deconvolution
# mini exam
Preparation and review the lecture by using online lecture notes. 200minutes
8. Image compression
# mini exam
Preparation and review the lecture by using online lecture notes. 200minutes
9. survey and examination preparation for examination 200minutes
10. Programming exercise (PC room): solve assignments. 400minutes
11. Programming exercise (PC room): solve assignments. 400minutes
12. Programming exercise (PC room): solve assignments. 400minutes
13. Programming exercise (PC room): solve assignments. 400minutes
14. Programming exercise (PC room): solve assignments. 400minutes
Total. - - 3800minutes
Feedback on exams, assignments, etc.
ways of feedback specific contents about "Other"
Feedback outside of the class (ScombZ, mail, etc.)
Textbooks and reference materials
参考書 : CG-Arts協会(画像情報教育進行委員会)『ディジタル画像処理[改訂新版] 大型本』 (in Japanese).
All the lecture notes will be uploaded at takashiijiri.com/classes/ about one week before the lecture. I recommend you to check them in advance.
Prerequisites
Recommend to make a study plan based on this syllabus and online lecture notes (takashiijiri.com/classes/).
Office hours and How to contact professors for questions
  • Friday 09:00-10:40
Regionally-oriented
Non-regionally-oriented course
Development of social and professional independence
  • Course that cultivates a basic problem-solving skills
  • Course that cultivates an ability for utilizing knowledge
  • Course that cultivates a basic self-management skills
Active-learning course
About half of the classes are interactive
Course by professor with work experience
Work experience Work experience and relevance to the course content if applicable
N/A N/A
Education related SDGs:the Sustainable Development Goals
  • 4.QUALITY EDUCATION
  • 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
Last modified : Sat Mar 14 14:20:21 JST 2026