Abstract
Adaptation of Zerotrees Using Signed Binary Digit Representations for 3D Image Coding
Highlights
Since the publication of the Grossmann and Morlet paper [1], theory and applications concerning wavelets have improved
Applications concerned mostly the data analysis field and more precisely in the timescale analysis. Their efficiency to represent complex signals with a limited number of generating functions raised an interest for image coding [4]
3D-embedded zerotree coding of wavelet coefficients (EZW)-nonadjacent form (NAF) is applied to a 256 × 256 × 224 extract of the scene 3 of f970620t01p02 r03 run from AVIRIS sensor on Moffett Field site
Summary
Since the publication of the Grossmann and Morlet paper [1], theory and applications concerning wavelets have improved. Applications concerned mostly the data analysis field and more precisely in the timescale analysis Their efficiency to represent complex signals with a limited number of generating functions raised an interest for image coding [4]. The quasiorthogonal 9/7 wavelet for lossy compression and the 5/3 wavelet for lossless compression with a multiresolution decomposition exhibit good results for a wide range of natural images. This paper looks at the zerotree-based compression techniques and improves them with the use of signed binary representations and arithmetic coding in the context of 3D image encoding. Hyperspectral images can be seen as three-dimensional data where two dimensions correspond to the spatial scene observed and the third dimension to the light spectrum for the pixel. All the details concerning the measures: distortion, bit rate are given later in Section 4, but all are common
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
