數據所(Institute of Data Science)

課程大綱(Course Outline)
本門課程的Programming assignment較多，請同學務必考量是否適合與能負荷。

The objective of this course is to introduce the students to the fundamental techniques and algorithms used for acquiring, processing, and extracting useful information from digital images. Particular emphasis will be placed on covering methods used for image sampling and quantization, image transforms, image enhancement and restoration, image encoding, image analysis, and pattern recognition. In addition, the students will learn how to apply the methods to solve real-world problems in several areas including medical, remote sensing, surveillance, and develop the insight necessary to use the tools of digital image processing (DIP) to solve any new problem.

1	Pretest: Programming skill test and fundamental of programming for DIP/CV
2	fundamental for image processing
3	Blurring, unsharp masking, Bilateral filter convolution
4	Image Processing in Frequency domain
5	Image recognition system overview
6	Global Features
7	Local Features: SIFT、SURF
8	Image representation PCA, DCT, LDA, NMF
9	Midterm
10	Feature learning Sparse representation
11	Face detection，Face detection viola&jones work
12	Face verification
13	Inpainting
14	High-dynamic-range image enhancement
15	Image super-resolution
16	Denoising and De-raining
17	Invited Talk
18	Final project