Arithmetic coding for data compression
Communications of the ACM
Techniques and standards for image, video, and audio coding
Techniques and standards for image, video, and audio coding
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Near-lossless image compression by relaxation-labelled prediction
Signal Processing - Image and Video Coding beyond Standards
Distributed Visual Information Management in Astronomy
Computing in Science and Engineering
Classified adaptive prediction and entropy coding for lossless coding of images
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
Fuzzy logic-based matching pursuits for lossless predictive coding of still images
IEEE Transactions on Fuzzy Systems
Applications of universal context modeling to lossless compression of gray-scale images
IEEE Transactions on Image Processing
Lossless image compression by quantization feedback in a content-driven enhanced Laplacian pyramid
IEEE Transactions on Image Processing
L∞ constrained high-fidelity image compression via adaptive context modeling
IEEE Transactions on Image Processing
The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS
IEEE Transactions on Image Processing
Lossless and Near-Lossless Image Compression Scheme Utilizing Blending-Prediction-Based Approach
ICCVG 2008 Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers
Lossless Compression Using Joint Predictor for Astronomical Images
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Spectral distortion in lossy compression of hyperspectral data
Journal of Electrical and Computer Engineering
Hi-index | 0.00 |
We describe an image compression strategy potentially capable of preserving the scientific quality of astrophysical data, simultaneously allowing a consistent bandwidth reduction to be achieved. Unlike strictly lossless techniques, by which moderate compression ratios are attainable, and conventional lossy techniques, in which the mean square error of the decoded data is globally controlled by users, near-lossless methods are capable of locally constraining the maximum absolute error, based on user's requirements. An advanced lossless/near-lossless differential pulse code modulation (DPCM) scheme, recently introduced by the authors and relying on a causal spatial prediction, is adjusted to the specific characteristics of astrophysical image data (high radiometric resolution, generally low noise, etc.). The background noise is preliminarily estimated to drive the quantization stage for high quality, which is the primary concern in most of astrophysical applications. Extensive experimental results of lossless, near-lossless, and lossy compression of astrophysical images acquired by the Hubble space telescope show the advantages of the proposed method compared to standard techniques like JPEG-LS and JPEG2000. Eventually, the rationale of virtually lossless compression, that is, a noise-adjusted lossles/near-lossless compression, is highlighted and found to be in accordance with concepts well established for the astronomers' community.