The new CCSDS image compression recommendation

Yeh, Pen-Shu; Armbruster, Philippe; Kiely, Aaron; Masschelein, Bart; Moury, Gilles; Schaefer, Christoph; Thiebaut, Carole

doi:10.1109/aero.2005.1559719

Cited by 42 publications

(12 citation statements)

References 5 publications

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“…However, the VM9 and the SGA both have a too high computational complexity for a coder on-board a satellite. Now, the BPE has a low complexity, since it has been designed to respect the on-board constraints [16] and it is quite easy to build a quasi-optimal bit allocation as suggested in [6] by just reading some tabulated values. In [24], the authors propose an extension to multicomponent images of the well-known 2-D SPIHT encoder [30] that has not the shortcoming of a high computational cost for bit-rate allocation.…”

Section: Bit-rate Computed With the Bpementioning

confidence: 99%

“…Thus, the concept of optimal coding transforms (OCT), under high resolution quantization hypothesis with entropy constrained scalar quantization and mean squared distortion, has been introduced in [14,15] and adapted to multicomponent images in [8][9][10]. Among various compression schemes associating spectral linear transforms and 2-D DWT, we focused on the separable scheme [10], which is compatible with both the JP2K Part2 standard and the CCSDS recommendations for on-board satellite image compression [16]. The separable scheme can be summarized as follows:…”

Section: Introductionmentioning

confidence: 99%

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Lossy and lossless compression of MERIS hyperspectral images with exogenous quasi-optimal spectral transforms

Barret¹

2010

J. Appl. Remote Sens

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International audienceOur research focuses on reducing complexity of hyperspectral image codecs based on transform and/or subband coding, so they can be on-board a satellite. It is well-known that the Karhunen Loeve transform (KLT) can be sub-optimal for non Gaussian data. However, it is generally recommended as the best calculable coding transform in practice. Now, for a compression scheme compatible with both the JPEG2000 Part2 standard and the CCSDS recommendations for onboard satellite image compression, the concept and computation of optimal spectral transforms (OST), at high bit-rates, were carried out, under low restrictive hypotheses. These linear transforms are optimal for reducing spectral redundancies of multi- or hyper-spectral images, when the spatial redundancies are reduced with a fixed 2-D discrete wavelet transform. The problem of OST is their heavy computational cost. In this paper we present the performances in coding of a quasi-optimal spectral transform, called exogenous OrthOST, obtained by learning an orthogonal OST on a sample of hyperspectral images from the spectrometer MERIS. Moreover, we compute an integer variant of OrthOST for lossless compression. The performances are compared to the ones of the KLT in both lossy and lossless compressions. We observe good performances of the exogenous OrthOST

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Section: Bit-rate Computed With the Bpementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Lossy and lossless compression of MERIS hyperspectral images with exogenous quasi-optimal spectral transforms

Barret¹

2010

J. Appl. Remote Sens

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“…As it has been specially designed for the compression on-board satellite, this algorithm can process the image in the strip-based mode and produces a fully embedded bit stream. This algorithm is currently being implemented on two ASICs by NASA Goddard and the University of Idaho [6,14]. This paper proposes an extension of the CCSDS-IDC algorithm to increase its compression performance for a small additive complexity.…”

Section: Introductionmentioning

confidence: 99%

“…At the time this paper is written and to the best of our knowledge, there have been very few attempts for an implementation of JPEG2000 on field programmable gate array (FPGA) [13,15] and still none on space qualified application-specific integrated circuits (ASIC). Facing this implementation problem, the CCSDS has issued in 2005 a new recommendation for on-board data compression: the CCSDS Image Data Compression (IDC) algorithm [1,14]. This algorithm is based on the DWT and on the very low complexity entropy coder bit plane encoder (BPE).…”

Section: Introductionmentioning

confidence: 99%

Satellite image compression by concurrent representations of wavelet blocks

et al. 2011

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This paper proposes a complete compression and coding scheme for on-board satellite applications considering the main on-board constraints: low computational power and easy bit rate control. The proposed coding scheme improves the performance of the current Consultative Committee for Space Data Systems (CCSDS) recommendation for a low additional complexity. We consider post-transforms in the wavelet domain, select the best representation for each block of wavelet coefficients, and encode it into an embedded bit stream. After applying a classical wavelet transform of the image, several concurrent representations of blocks of wavelet coefficients are generated. The best representations are then selected according to a ratedistortion criterion. Finally, a specific bit-plane encoder derived from the CCSDS recommendation produces an embedded bit stream ensuring the easy rate control required. In this article, both the post-transforms and This work has been carried out under the financial support of the French space agency CNES (www.cnes.fr) and NOVELTIS company (www.noveltis.fr).X. Delaunay NOVELTIS, Parc technologique du canal, 2 av. de l'Europe, the best representation selection have been adapted to the low complexity constraint, and the CCSDS coder has been modified to compress post-transformed representations.

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“…Since the CCSDS 122.0-B-1 Image Data Compression [24,133] standard recommendation represents a good trade-off between compression performance and implementation complexity, it was selected as basis algorithm for this thesis. It is a wavelet-based image data compression algorithm and often just called CCSDS-IDC 28 .…”

Section: The Ccsds 1220-b-1 Image Compression Standardmentioning

confidence: 99%

Reconfigurable architecture for real-time image compression on-board satellites

Manthey

Krutz

Juurlink

2015

J. Appl. Remote Sens

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Data products of optical remote sensing systems are increasingly used in many areas of our everyday life. The spatial as well as the spectral resolution of satellite image data increases steadily with new missions resulting in a higher precision of known procedures and new application scenarios. While the memory capacity requirements can still be fulfilled, the transmission capacity becomes increasingly problematic. Real-time transmission of high-resolution image data is currently not possible.This thesis presents a new image data compression architecture that can be used for current and future projects at the German Aerospace Center (DLR). The architecture has region-of-interest support and offers flexible access to the compressed data based on the CCSDS 122.0-B-1 image data compression standard. Region of interest (ROI) coding can be useful in scenarios where on-board classification, registration, or object or change detection algorithms are used. It is also useful to decrease the amount of data that must be transferred to the ground station. Modifications to the standard have been made to permit a change of compression parameters and the re-organization of the bit-stream after compression. An additional index of the compressed data is created, which makes it possible to locate individual parts of the bit-stream. On request, compressed and stored images can be re-assembled and transmitted according to the application's needs and as requested by the ground station.The requirements, the design of the architecture, and its implementation based on reconfigurable hardware are presented. The architecture was developed for a spacequalified Xilinx Virtex 5QV, where a single instance of the architecture is capable of compressing images at a rate of up to 200 Mpx /s (or 400 Mbyte /s for 16 bit images). It operates at a clock frequency of 100 MHz and processes two image pixels per clock cycle. A Xilinx Virtex-5QV enables thereby compressing images with a width of up to 4096 pixels without the use of external memory. Without external memory and additional interfaces, the power consumption of the architecture is about 5 W. The proposed architecture is one of the fastest implementations yet reported and sufficient for recent high-resolution systems. Investigations in the resource and power consumption, as well as the availability of external storage have shown that it should be possible to integrate the design directly on a focal plane.

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The new CCSDS image compression recommendation

Cited by 42 publications

References 5 publications

Lossy and lossless compression of MERIS hyperspectral images with exogenous quasi-optimal spectral transforms

Lossy and lossless compression of MERIS hyperspectral images with exogenous quasi-optimal spectral transforms

Satellite image compression by concurrent representations of wavelet blocks

Reconfigurable architecture for real-time image compression on-board satellites

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