Lossy-to-Lossless Hyperspectral Image Compression Based on Multiplierless Reversible Integer TDLT/KLT

• Published in: IEEE geoscience and remote sensing letters Vol. 6; no. 3; pp. 587 - 591
• Main Authors: Lei Wang, Lei Wang, Jiaji Wu, Jiaji Wu, Licheng Jiao, Licheng Jiao, Guangming Shi, Guangming Shi
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2009; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Compressing; Costs; Decorrelation; Discrete cosine transform (DCT); Discrete cosine transforms; Discrete transforms; Discrete wavelet transforms; Factorization; hyperspectral image compression; Hyperspectral imaging; Hyperspectral sensors; Image coding; Image compression; integer transform; Integers; Karhunen-Loeve transforms; Karhunen-LoÈve transform (KLT); lossy-to-lossless compression; Mathematical models; Spectra; Time domain analysis; time-domain lapped transform (TDLT); Transforms
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2009.2021674

We proposed a new transform scheme of multiplierless reversible time-domain lapped transform and Karhunen-Loeve transform (RTDLT/KLT) for lossy-to-lossless hyperspectral image compression. Instead of applying discrete wavelet transform (DWT) in the spatial domain, RTDLT is applied for decorrelation. RTDLT can be achieved by existing discrete cosine transform and pre- and postfilters, while the reversible transform is guaranteed by a matrix factorization method. In the spectral direction, reversible integer low-complexity KLT is used for decorrelation. Owing to completely reversible transform, the proposed method can realize progressive lossy-to-lossless compression from a single embedded code-stream file. Numerical experiments on benchmark images show that the proposed transform scheme performs better than 5/3DWT-based methods in both lossy and lossless compressions, comparable with the optimal 9/7DWT-FloatKLT-based lossy compression method.