Vector quantization and signal compression
Vector quantization and signal compression
Matrix computations (3rd ed.)
Kronecker-product gain-shape vector quantization for multispectral and hyperspectral image coding
IEEE Transactions on Image Processing
Compression of multispectral images by spectral classification and transform coding
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
Lossy-to-lossless 3D image coding through prior coefficient lookup tables
Information Sciences: an International Journal
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Compression of remote-sensing images can be necessary in various stages of the image life, and especially on-board a satellite before transmission to the ground station. Although on-board CPU power is quite limited, it is now possible to implement sophisticated real-time compression techniques, provided that complexity constraints are taken into account at design time. In this paper we consider the class-based multispectral image coder originally proposed in [Gelli and Poggi, Compression of multispectral images by spectral classification and transform coding, IEEE Trans. Image Process. (April 1999) 476-489 [5]] and modify it to allow its use in real time with limited hardware resources. Experiments carried out on several multispectral images show that the resulting unsupervised coder has a fully acceptable complexity, and a rate-distortion performance which is superior to that of the original supervised coder, and comparable to that of the best coders known in the literature.