Course title
L03652002
Digital Media Processing

IJIRI Takashi Click to show questionnaire result at 2018
Course description
Image processing is indispensable for various fields, including industry, natural science, entertainment, and so on. This class, Digital Media Processing 1, 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.

(*)Lecture notes are available from Ijiri's web page (takashiijiri.com) and lecture videos will be available from Microsoft stream.
(*)Lecture style may change depending on the prevalence of COVID19 and social conditions.
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.

Lecture notes are available at takashiijiri.com.
Lecture videos are also available on Microsoft Stream.
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.
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 Preparation and review the lecture by using online lecture notes. 200minutes
2. Introduction 2: Digital camera, human vision, color Preparation and review the lecture by using online lecture notes. 200minutes
3. Filtering 1: tone curve, linear filters Preparation and review the lecture by using online lecture notes. 200minutes
4. Filtering 2: non-linear filters, halftoning Preparation and review the lecture by using online lecture notes. 200minutes
5. Filtering 3: DFT, frequency filters Preparation and review the lecture by using online lecture notes. 200minutes
6. Geometric transform : affine transform and image interpolation Preparation and review the lecture by using online lecture notes. 200minutes
7. Convolution and deconvolution Preparation and review the lecture by using online lecture notes. 200minutes
8. Image compression Preparation and review the lecture by using online lecture notes. 200minutes
9. Examination prepare for the 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
15.
Total. - - 3800minutes
Relationship between 'Goals and Objectives' and 'Course Outcomes'

programing assignment Examination minute paper and daily test Total.
1. 5% 10% 3% 18%
2. 5% 10% 3% 18%
3. 5% 10% 2% 17%
4. 5% 10% 2% 17%
5. 30% 30%
Total. 50% 40% 10% -
Evaluation method and criteria
By minute papers (10%), examinations (40%), and assignments (50%).
-- The examination 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%)
+ developmental assignments (40%)
with respect to image processing and image recognition.
Textbooks and reference materials
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 you 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 10:40-12:30
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
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
  • 17.PARTNERSHIPS FOR THE GOALS
Last modified : Tue Aug 16 04:03:35 JST 2022