A tutorial on modern lossy wavelet image compression: foundations of JPEG 2000
By Bryan Usevitch. IEEE Signal Processing Magazine, 2001
505 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/3d3bcab4be6cc68066fb47a08b59a918ac3813e6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Vivek K Goyal
- Charilaos A. Christopoulos
- Touradj Ebrahimi
- Athanassios N. Skodras
- Jean‐Michel Poggi
- Michel Misiti
- Georges Oppenheim
- Yves Misiti
In Signal Processing
- Touradj Ebrahimi
- Athanassios N. Skodras
- Charilaos A. Christopoulos
- Jean‐Michel Poggi
- Vivek K Goyal
- Michel Misiti
- Georges Oppenheim
- Yves Misiti
Citations in the corpus
- Wavelets and their applications (2007, methodology): “For compression and, in particular compression of images, we may refer to [DEV 92] for general ideas, to [BRI 95] for application to fingerprints and [USE 01] and [JPE 00] for the standard JPEG 2000.”
- Theoretical foundations of transform coding (2001, methodology): “This is discussed in detail in two articles of this Magazine [37], [38].”
- Multiple description coding: compression meets the network (2001, background): “Embedded coding allows the compressed data to be cut off at any point with commensurate image quality [95].”
- The JPEG 2000 still image compression standard (2001, methodology): “For both modes to be implemented , the signal should first be extended periodically as has been demonstrated in the previous article by Usevitch [70] (Fig.”