An overview of the JPEG 2000 still image compression standard
By Majid Rabbani, Rajan L. Joshi. 2002
861 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Signal Processing
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
- Dacheng Tao
- Luc Van Gool
- Kilian Q. Weinberger
- Trevor Darrell
- Jitendra Malik
- Xiaogang Wang
- Yi Yang
- Alan L. Yuille
In Signal Processing
- James T. Wilson
- Masaru Takeuchi
- Oren Rippel
- Lubomir D. Bourdev
- Jiro Katto
- Stephen Tyree
- Heming Sun
- Zhengxue Cheng
Citations in the corpus
- Compressing Convolutional Neural Networks in the Frequency Domain (2015, methodology): “Methods built on the DCT are widely used for compressing images and movies, including forming the standard technique for JPEG [29].”
- Real-Time Adaptive Image Compression (2017, methodology): “The JPEG 2000 standard, for example, employs discrete wavelet transforms with the Daubechies 9/7 kernels (Antonini et al., 1992; Rabbani & Joshi, 2002).”
- Learned Image Compression With Discretized Gaussian Mixture Likelihoods and Attention Modules (2020, methodology): “Classical image compression standards include JPEG [1], JPEG2000 [2], HEVC/H.265 [3] and ongoing Versatile Video Coding (VVC) [4] which will be the next generation compression standard expected by the end of 2020.”
- A Tutorial of the Wavelet Transform (2010, neutral): “An overview of the JPEG 2000 system can be found in [12], [13].”