You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
1 November 1993Optimal thresholding in wavelet image compression
Wavelet transform coding has the potential to offer a lot of benefits with respect to image compression and image filtering as well. The later aspect is of importance in machine processing of high entropy images such as Synthetic Aperture Radar images obtained by the European Remote sensing Satellite (ERS-1). A mathematical model is developed to study the relation between a specified Mean Square Error, the value of the wavelet coefficient threshold and the maximum number of resolutions used. The wavelet compression method is compared with other compression methods like JPEG standard and Vector Quantization for a number of different (in a statistical sense) images amongst others LENA.
The alert did not successfully save. Please try again later.
F. O. Zeppenfeldt, J. B. Boerger, A. Koppes, "Optimal thresholding in wavelet image compression," Proc. SPIE 2034, Mathematical Imaging: Wavelet Applications in Signal and Image Processing, (1 November 1993); https://doi.org/10.1117/12.162067