Transform Based Lossy Compression of Multispectral Images

Kaarna, Arto; Parkkinen, Jussi

doi:10.1007/pl00010985

Cited by 23 publications

(16 citation statements)

References 23 publications

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“…Examples include the Joint Photographic Experts Group (JPEG) 2000 standard [1], and set partitioning methods such as set partitioning in hierarchical trees (SPIHT) and its variations [SPIHT-2D, SPIHT-3D, set partitioned embedded block (SPECK)]. Some authors have also proposed to employ the 3-D discrete wavelet transform (DWT) [2]- [4] and the 3-D discrete cosine transform (DCT) [5], [6].…”

mentioning

confidence: 99%

Transform Coding Techniques for Lossy Hyperspectral Data Compression

Penna

Tillo

Magli

et al. 2007

IEEE Trans. Geosci. Remote Sensing

272

153

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Abstract-Transform-based lossy compression has a huge potential for hyperspectral data reduction. Hyperspectral data are 3-D, and the nature of their correlation is different in each dimension. This calls for a careful design of the 3-D transform to be used for compression. In this paper, we investigate the transform design and rate allocation stage for lossy compression of hyperspectral data. First, we select a set of 3-D transforms, obtained by combining in various ways wavelets, wavelet packets, the discrete cosine transform, and the Karhunen-Loève transform (KLT), and evaluate the coding efficiency of these combinations. Second, we propose a low-complexity version of the KLT, in which complexity and performance can be balanced in a scalable way, allowing one to design the transform that better matches a specific application. Third, we integrate this, as well as other existing transforms, in the framework of Part 2 of the Joint Photographic Experts Group (JPEG) 2000 standard, taking advantage of the high coding efficiency of JPEG 2000, and exploiting the interoperability of an international standard. We introduce an evaluation framework based on both reconstruction fidelity and impact on image exploitation, and evaluate the proposed algorithm by applying this framework to AVIRIS scenes. It is shown that the scheme based on the proposed low-complexity KLT significantly outperforms previous schemes as to rate-distortion performance. As for impact on exploitation, we consider multiclass hard classification, spectral unmixing, binary classification, and anomaly detection as benchmark applications.

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mentioning

confidence: 99%

Transform Coding Techniques for Lossy Hyperspectral Data Compression

Penna

Tillo

Magli

et al. 2007

IEEE Trans. Geosci. Remote Sensing

272

153

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“…In [12] Kaarna and Parkkinen recommend a short wavelets basis as a good choice for spectral wavelets. This recommendation is confirmed by the results obtained by Mansouri et al in [13] in which the authors propose the Haar lifting scheme wavelets basis as an appropriate short support basis for reflectance representation and estimation from multispectral images.…”

Section: Second Strategy -Full 3dmentioning

confidence: 99%

Comparative study of multi-2D, Full 3D and hybrid strategies for multi/hyperspectral image compression

Delcourt

Mansouri

Sliwa

et al. 2009

2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis

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In this paper, we investigate appropriate strategies for multi/hyperspectral image compression. In particular, we compare the classic multi-2D compression strategy and two different implementations of 3D strategies (Full 3D and hybrid). All strategies are combined with a PCA decorrelation stage to optimize performance. For multi-2D and hybrid strategies, we propose a weighted version of PCA. Finally, for consistent evaluation, we propose a larger comparison framework than the conventionally used PSNR. The results are significant and show the weaknesses and strengths of each strategy.

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“…Although many multispectral compression algorithms have been proposed [5], [6], [7], [8], to the best of our knowledge, the compression of RGB and NIR has not been specifically addressed so far. Therefore we propose a novel framework for RGB+NIR (RGBN) image compression.…”

Section: Introductionmentioning

confidence: 99%

“…Fowler and Rucker [5] argue against the performance of these compression approaches, because such methods do not take the specific characteristics of such data into account. To explore this potential, [5], [6] and [12] employ a two-stage process. First, the spectral correlation is removed, then the spatial correlation is exploited.…”

Section: Introductionmentioning

confidence: 99%

Compression of multispectral images: Color (RGB) plus near-infrared (NIR)

Salamati

Sadeghipoor

Süsstrunk

2012

2012 IEEE 14th International Workshop on Multimedia Signal Processing (MMSP)

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Abstract-We propose a compression framework for fourchannel images, composed of color (RGB) and near-infrared (NIR) channels, which exploits the correlation between the visible and the NIR information. The high-frequency components of both visible and NIR scene representations are strongly correlated. By encoding only the DCT components that differ above a chosen threshold, we significantly improve compression ratios for a given quality level. To evaluate our proposed method, we compare our results with standard JPEG compression, as well as PCA-based approaches that are often employed to compress multispectral images. Our experiments show that applying our proposed method yields the same quality at a lower bit-rate, compared to conventional JPEG and PCA-based algorithms.

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Transform Based Lossy Compression of Multispectral Images

Cited by 23 publications

References 23 publications

Transform Coding Techniques for Lossy Hyperspectral Data Compression

Transform Coding Techniques for Lossy Hyperspectral Data Compression

Comparative study of multi-2D, Full 3D and hybrid strategies for multi/hyperspectral image compression

Compression of multispectral images: Color (RGB) plus near-infrared (NIR)

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