1. Introduction to multidimensional signal processing
2-D convolution and filtering
2-D discrete-time Fourier transform
2-D sampling and reconstruction
2. Transforms
DFT
DCT
KLT
Wavelets and Directional Transforms
3. Applications:
Image Coding
Optical Flow, Motion Estimation and Video Coding
Image Quality Assessment
Enhancement, Restoration, and Denoising
Edge/point/line Detection
Retrieval and Similarity Indexes
Saliency and Attention Models
4. Machine Learning for Images
Intro. to Machine Learning and its Applications in Image Processing
Basis Functions for Images and Autoencoders
Fund. of Linear Classifiers and SVMs
Basics of CNNs and Recent Applications in Image Classifications
Scene Labeling (Supervised and Weakly Supervised)
Overview of LSTM, RNN, and NTM for Image-related Applications
5. Color Processing
Color Space
Color Conversion
Color Component Transportation
6. Recent Trends in Image Processing
