Iterative Hillclimbing Optimization Techniques for Transform Image Encoding/Decoding and for Image Segmentation

Open Access
Bunyaratavej, Piya
Graduate Program:
Electrical Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
May 23, 2002
Committee Members:
  • Jia Li, Committee Member
  • John F Doherty, Committee Member
  • David Jonathan Miller, Committee Chair
  • George Kesidis, Committee Member
  • John Metzner, Committee Member
  • image segmentation
  • image decoding
  • optimization
  • image encoding
  • iterative
  • hillclimbing
An iterative hillclimbing optimization technique was introduced in this thesis. It was used to tackle many index assignment problems, i.e. transform image encoding, noisy image decoding, and image segmentation. We first studied basic transform image coding techniques, then introduced an iterative algorithm which has a hillclimbing property on the cost function. We then extended the algorithm to hyperspectral image coding. We realized that the algorithm can be generalized to other applications as well. We applied the iterative hillclimbing idea to noisy channel image decoding. We also investigated a Turbo-like joint source-channel decoding technique, which is another kind of iterative decoding. Lastly, we re-investigated the image segmentation application, using the iterat$ The hillclimbing method inspired development of another iterative algorithm whi$ with applications both to image decoding and image segmentation. The hillclimbing algorithm at the heart of this thesis thus yielded several promising offshoot directions for continuing research.