Project Description:
Image compression is a process of reducing redundancy of the image data in order to store and transmit data efficiently. In this project, we will study different image compression techniques such as singular value decomposition (SVD), discrete cosine transforms (DCT) and Gaussian pyramids, with a systematic comparison between different approaches. Lastly, we will explore the possibility of applying these compression algorithms to surface data.

Tentative schedule:
TBA

Reading materials: (will be updated regularly)

• Basic introduction to image compression
• Website: Introduction to image compression by Satish Kumar
• PDF Slide: Image compression basics by Brower
  
• PDF Slide: Introduction to Still Image Compression by Peleg

• SVD  based image compression
• PDF: SVD applied to digital image processing by Cao

• Discrete fourier transform and discrete cosine trasnform
• PDF: Image compression and DCT by Cabeen
• PDF: DCT: theories and applications by Khayam
• PDF: Discrete fourier transform
• PDF: Introduction to fourier theories
• PDF Slide: Basics of DCT, Quantization and Entropy Coding by Peleg