Content-aware adaptive compression of satellite imagery using artificial vision
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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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