APPLICATION OF EOFS TO MULTISPECTRAL IMAGERY COMPRESSION

Award Information
Agency:
National Aeronautics and Space Administration
Branch
n/a
Amount:
$49,948.00
Award Year:
1991
Program:
SBIR
Phase:
Phase I
Contract:
n/a
Award Id:
16981
Agency Tracking Number:
16981
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
840 Memorial Dr, Cambridge, MA, 02139
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
() -
Business Contact:
() -
Research Institution:
n/a
Abstract
INCREASES IN INFORMATION BANDWIDTH USING COMMUNICATION CHANNELS OF FIXED PHYSICAL BANDWIDTH ARE MADE POSSIBLE BY ELIMINATING REDUNDANT INFORMATION IN THE INFORMATION STREAM USING DATA COMPRESSION-DECOMPRESSION ALGORITHMS. IMAGES--ESPECIALLY MULTISPECTRAL OR COLOR IMAGES--PUT THE GREATEST STRAIN ON COMMUNICATIONS CHANNELS. A VARIETY OF EXISTING TECHNIQUES, OF VARYING MATURITY, MAY BE APPLIED TO THE PROBLEM OF IMAGE COMPRESSION. SEVERAL OF THESE TECHNIQUES MAY BE APPLIED TO MULTISPECTRAL IMAGES, BUT THEY ARE LESS THAN OPTIMAL. THE APPROACH IN THIS PROJECT FIRST COMPRESSES THE DATA SPECTRALLY TO DERIVE ORTHOGONAL IMAGES WITH MINIMUM BIT DEPTH. THIS TECHNIQUE IS ADAPTIVE AND MAKES USE OF EMPIRICAL ORTHOGONAL FUNCTIONS. AFTER BEING SPECTRALLY COMPRESSED, THE DATA ARE FURTHER COMPRESSED USING STANDARD TECHNIQUES, SUCH AS TRANSFORM CODING, VECTOR QUANTIZATION, AND DCPM. THE EFFICIENCY OF THE LOSS SCHEMES STUDIED WILL BE ASSESSED BY STANDARD STATISTICAL MEASURES, AS WELL AS BY CONSIDERING THE EFFECT OF THE COMPRESSION ON END-USER ALGORITHMS, SUCH AS CLOUD PARAMETER EXTRACTION AND SPECTRAL FEATURE IDENTIFICATION. INCREASES IN INFORMATION BANDWIDTH USING COMMUNICATION CHANNELS OF FIXED PHYSICAL BANDWIDTH ARE MADE POSSIBLE BY ELIMINATING REDUNDANT INFORMATION IN THE INFORMATION STREAM USING DATA COMPRESSION-DECOMPRESSION ALGORITHMS. IMAGES--ESPECIALLY MULTISPECTRAL OR COLOR IMAGES--PUT THE GREATEST STRAIN ON COMMUNICATIONS CHANNELS. A VARIETY OF EXISTING TECHNIQUES, OF VARYING MATURITY, MAY BE APPLIED TO THE PROBLEM OF IMAGE COMPRESSION. SEVERAL OF THESE TECHNIQUES MAY BE APPLIED TO MULTISPECTRAL IMAGES, BUT THEY ARE LESS THAN OPTIMAL. THE APPROACH IN THIS PROJECT FIRST COMPRESSES THE DATA SPECTRALLY TO DERIVE ORTHOGONAL IMAGES WITH MINIMUM BIT DEPTH. THIS TECHNIQUE IS ADAPTIVE AND MAKES USE OF EMPIRICAL ORTHOGONAL FUNCTIONS. AFTER BEING SPECTRALLY COMPRESSED, THE DATA ARE FURTHER COMPRESSED USING STANDARD TECHNIQUES, SUCH AS TRANSFORM CODING, VECTOR QUANTIZATION, AND DCPM. THE EFFICIENCY OF THE LOSS SCHEMES STUDIED WILL BE ASSESSED BY STANDARD STATISTICAL MEASURES, AS WELL AS BY CONSIDERING THE EFFECT OF THE COMPRESSION ON END-USER ALGORITHMS, SUCH AS CLOUD PARAMETER EXTRACTION AND SPECTRAL FEATURE IDENTIFICATION.

* information listed above is at the time of submission.

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