Preserving radiometric resolution in remotely sensed data with lossy compression

• Published in: IEEE transactions on geoscience and remote sensing Vol. 35; no. 5; pp. 1171 - 1176
• Main Authors: Tilton, J.C., Manohar, M.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01-09-1997; Institute of Electrical and Electronics Engineers
• Subjects: Applied geophysics; Channel capacity; Downlink; Earth sciences; Earth, ocean, space; Exact sciences and technology; High-resolution imaging; Image coding; Internal geophysics; NASA; Radiometry; Rate-distortion; Satellite broadcasting; Spatial resolution; Transform coding; United States; satellites; Thematic Mapper; Space remote sensing; Landsat; satellite methods; North America; Earth; imagery; radiometry; spatial resolution; data acquisition; compression; Pixel; high resolution
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/36.628784

Recent advances in imaging technology make it possible to obtain remotely sensed imagery data of the Earth at high spatial, spectral, and radiometric resolutions. The rate at which the data is collected from these satellites can far exceed the channel capacity of the data downlink. Reducing the data rate to within the channel capacity can often require painful trade-offs in which certain scientific returns are sacrificed for the sake of others. The authors focus on the case where radiometric resolution is sacrificed by dropping a specified number of lower order bits (LOB) from each data pixel. To limit the number LOBs dropped, they also compress the remaining bits using lossless compression. They call this approach "truncation followed by lossless compression" or TLLC. They then demonstrate the suboptimality of this TLLC approach by comparing it with the direct application of a more effective lossy compression technique based on the JPEG algorithm. This comparison demonstrates that, for a given channel rate, the method based on JPEG lossy compression better preserves radiometric resolution than does TLLC.