In this paper, we investigate low-complexity encryption solutions to be embedded in the recently proposed CCSDS standard for lossless and near-lossless multispectral and hyperspectral image compression. The proposed approach is based on the randomization of selected components in the image compression pipeline, namely the sign of prediction residual and the fixed part of Rice-Golomb codes, inspired by similar solutions adopted in video coding. Thanks to the adaptive nature of the CCSDS algorithm, even simple randomization of the sign of prediction residuals can provide a sufficient scrambling of the decoded image when the encryption key is not available. Results on the standard CCSDS test set show that the proposed technique uses on average...
This paper considers an approach to the compression of hyperspectral remote sensing data by an origi...
With the rapid developments in the remote sensing technologies and services, there is a necessity fo...
Remote sensing sensors are used in various applications from Earth sciences, archeology, intelligenc...
Multispectral and hyperspectral image data payloads have large size and may be challenging to downlo...
This paper describes the emerging Issue 2 of the CCSDS-123.0-B standard for low-complexity compressi...
Predictive lossy compression has been shown to represent a very flexible framework for lossless and ...
This article studies the performance impact related to different parameter choices for the new CCSDS...
Abstract-Public policies and private initiatives share the will to explore outer space and to monito...
The goal of this work is to study the feasibility of a low-complexity encoder for lossless compressi...
New multispectral and hyperspectral instruments are going to generate very high data rates due to th...
The capacity of the downlink channel is a major bottleneck for applications based on remote sensing ...
In this paper we propose a lossless and lossy onboard compression algorithm for multispectral and hy...
Predictive coding is attractive for compression onboard of spacecrafts thanks to its low computation...
In this paper we propose a lossless compression algorithm for hyperspectral images based on distribu...
International audienceWe report on a new algorithm to compress and encrypt simultaneously multiple i...
This paper considers an approach to the compression of hyperspectral remote sensing data by an origi...
With the rapid developments in the remote sensing technologies and services, there is a necessity fo...
Remote sensing sensors are used in various applications from Earth sciences, archeology, intelligenc...
Multispectral and hyperspectral image data payloads have large size and may be challenging to downlo...
This paper describes the emerging Issue 2 of the CCSDS-123.0-B standard for low-complexity compressi...
Predictive lossy compression has been shown to represent a very flexible framework for lossless and ...
This article studies the performance impact related to different parameter choices for the new CCSDS...
Abstract-Public policies and private initiatives share the will to explore outer space and to monito...
The goal of this work is to study the feasibility of a low-complexity encoder for lossless compressi...
New multispectral and hyperspectral instruments are going to generate very high data rates due to th...
The capacity of the downlink channel is a major bottleneck for applications based on remote sensing ...
In this paper we propose a lossless and lossy onboard compression algorithm for multispectral and hy...
Predictive coding is attractive for compression onboard of spacecrafts thanks to its low computation...
In this paper we propose a lossless compression algorithm for hyperspectral images based on distribu...
International audienceWe report on a new algorithm to compress and encrypt simultaneously multiple i...
This paper considers an approach to the compression of hyperspectral remote sensing data by an origi...
With the rapid developments in the remote sensing technologies and services, there is a necessity fo...
Remote sensing sensors are used in various applications from Earth sciences, archeology, intelligenc...