International Journal of Scientific Research and Engineering Development

Image compression of Hyperspectral data is necessary because of the large storage requirements. The algorithms developed in this paper are compared in terms of compression performance and computational complexity against the best existent algorithms. The algorithms are Kalman Spectral Prediction (KSP) algorithm and Low Complexity Lossless Compression for Image (LOCO-I) algorithm. In this KSP is a Band Sequential (BSQ) format and LOCO-I is a Band Interleaved by Line (BIL) format. The band sequential format requires that all data for a single band covering the entire scene be written as one file. In band interleaved by line format, the data for the bands are written line by line onto the same tape. Many researches like this format because it is not necessary to read serially past unwanted information if certain bands are of no value. It is useful format if all the bands are to be used in the analysis. If some bands are not of interest, the format is inefficient. In this we compare the two different formats of data. LOCO-I uses the information of only one previous band for prediction stage. However, the KSP algorithm alternates the information of more than one previous band for prediction. In this KSP algorithm performs greater compression ratio than LOCO algorithm because KSP algorithm uses more than one band for the prediction. In this LOCO algorithm compress the input data half of its size but KSP algorithm compress the data more than half of its size. The time complexity of KSP algorithm is less compared to LOCO algorithm. The compression ratio for the KSP algorithm is 61% but the compression ratio for LOCO algorithm is 55%. KSP algorithm is more efficient because it gives the spectral characteristics of the data using the interband prediction.

Sabitha Kumari.N,"A Novel Approach for Hyperspectral Lossless Image Compression" International Journal of Scientific Research and Engineering Development, V9(1): Page(867-874) Jan-Feb 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.