Digital Image Processing (3-0-3)

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