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Undergraduate Research Project Management System

Bio-Inspired Intelligent Satellite Image Compression

Status Current
Seeking Researchers No
Start Date 03/01/2009
End Date 04/30/2010
Funding Source OURS
Funding Amount 1,000
Community Partner
Related Course
Last Updated 05/02/2009 02:37AM
Keywords Image processing, evolutionary computation, wavelets, optimization, quantization

People

Faculty
  Frank Moore, Michael Peterson

Student Researchers
  Britny Herzog

Abstract

The purpose of this research project is to demonstrate the technical feasibility of using evolutionary and bio-inspired optimization techniques to identify new coding and transform algorithms for optimized satellite data (e.g., image) communication (SATCOM) and for transmission of image data among unmanned aerial vehicles (UAVs) across bandwidth-limited channels. Extending previous success in the areas of satellite, fingerprint and photograph compression and reconstruction under conditions subject to data loss due to quantization, this research will optimize sets of transform-defining filter coefficients optimized for satellite image processing. This project seeks to develop new image compression algorithms that outperform the current state of the art techniques for satellite image compression. The optimized image compression algorithms replace the traditional wavelet algorithms currently employed in state-of-the-art signal processing systems. We compare optimized transforms with traditional wavelet-based transforms to determine the reduction in the number of bits required for robust transmission of satellite-captured images across narrow bandwidth channels. Because optimized compression algorithms simply replace existing wavelet filter coefficients without altering the underlying transform algorithm, this approach enables higher SATCOM capacity without incurring costly hardware modifications.

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