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<p>This thesis aims to improve image throughput from satellite to Earth by using Artificial Vision to perform data compression before the downlink. Onboard Analysis for Selective Imagery Compression (OASIC) is a hybrid compression algorithm designed for oceanic imagery, incorporating
both lossless and lossy compression methods to achieve a high compression ratio
with minimal noise on vessels of interest. This is achieved by separating the vessels from
the surrounding ocean and storing them with high fidelity, while compressing the remainder
of the image with low fidelity. The performance of OASIC is examined on full resolution
panchromatic satellite images and compared to both lossless and lossy JPEG2000 compressed
images. In nearly all configurations tested, OASIC outperforms JPEG2000, achieving an average
fifteen-fold improvement in compression ratios while maintaining a nearly lossless fidelity
for the vessels within the OASIC compressed images. This content-sensitive compression algorithm
can potentially enable the transmission of higher spatial resolution images, with more
spectral bands, and at higher download speeds from space.
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<br>Subjects: Lossless Image Compression, Lossy Image Compression, Ship Detection, Support Vector Machine, Discrete Wavelet Transform, Artificial Vision, Satellite Imagery</div>
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Wilcox, Jeffrey</div>
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