Abstract
An effective lossy algorithm for compressing hyperspectral images using singular value decomposition (SVD) and discrete cosine transform (DCT) has been proposed. A hyperspectral image consists of a number of bands where each band contains some specific information. This paper suggests compression algorithms that compress the hyperspectral images by considering image data, band by band and compress each band employing SVD and DCT. The compression performance of the resultant images is evaluated using various objective image quality metrics.
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Srinivas Vadali, Deekshitulu, G.V.S.R., Murthy, J.V.R. (2016). Optimization of Hyperspectral Images and Performance Evaluation Using Effective Loss Algorithm. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 436. Springer, Singapore. https://doi.org/10.1007/978-981-10-0448-3_77
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DOI: https://doi.org/10.1007/978-981-10-0448-3_77
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