MULTIDIMENSIONAL ROTATIONS FOR ROBUST QUANTIZATION OF IMAGE DATA

Authors
Citation
Ac. Hung et Th. Meng, MULTIDIMENSIONAL ROTATIONS FOR ROBUST QUANTIZATION OF IMAGE DATA, IEEE transactions on image processing, 7(1), 1998, pp. 1-12
Citations number
54
Categorie Soggetti
Computer Science Software Graphycs Programming","Computer Science Theory & Methods","Engineering, Eletrical & Electronic","Computer Science Software Graphycs Programming","Computer Science Theory & Methods
ISSN journal
10577149
Volume
7
Issue
1
Year of publication
1998
Pages
1 - 12
Database
ISI
SICI code
1057-7149(1998)7:1<1:MRFRQO>2.0.ZU;2-I
Abstract
Laplacian and generalized Gaussian data arise in the transform and sub band coding of images, This paper describes a method of rotating indep endent, identically distributed (i.i.d.) Laplacian-like data in multip le dimensions to Significantly improve the overload characteristics fo r quantization, The rotation is motivated by the geometry of the Lapla cian probability distribution, and can be achieved with only additions and subtractions using a Walsh-Hadamard transform, Its theoretical an d simulated results for scalar, lattice, and polar quantization are pr esented in this paper, followed by a direct application to image compr ession, We show that rotating the image data before quantization not o nly improves compression performance, but also increases robustness to the channel noise and deep fades often encountered in wireless commun ication.