Wavelet transform for image data compression

Author

Hamidi, Seyed M. ; Adhami, Reza R.

Author_Institution

Dept. of Electr. & Comput. Eng., Alabama Univ., Huntsville, AL, USA

fYear

1994

fDate

20-22 Mar 1994

Firstpage

462

Lastpage

465

Abstract

Derives a new compactly supported wavelet using the Daubechies approach. The construction of a “mother wavelet” is based on the notion of multiresolution analysis and is derived using the theory of compactly supported wavelet bases. The FIR filter related to this wavelet has 22 taps which leads to a regular wavelet with a high number of vanishing moments. The new wavelet and its dilated and shifted versions serve as a basis function for the measurable, square-integrable functions space L²(R). To construct an orthonormal basis function for L²(R²), the authors simply take two one-dimensional bases and form the tensor product function. The new basis function is then implemented in a discrete form, and is used to decorrelate the data in an image, followed by a data compression scheme

Keywords

data compression; digital filters; filtering and prediction theory; image coding; wavelet transforms; Daubechies approach; FIR filter; basis function; compactly supported wavelet; data compression scheme; data decorrelation; dilated version; image data compression; mother wavelet; multiresolution analysis; one-dimensional bases; orthonormal basis function; shifted version; square-integrable functions space; taps; tensor product function; vanishing moments; Data compression; Discrete wavelet transforms; Filter bank; Filtering; Finite impulse response filter; Image coding; Multiresolution analysis; Polynomials; Wavelet analysis; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

System Theory, 1994., Proceedings of the 26th Southeastern Symposium on

Conference_Location

Athens, OH

ISSN

0094-2898

Print_ISBN

0-8186-5320-5

Type

conf

DOI

10.1109/SSST.1994.287832

Filename

287832