Differential encoding of high-resolution data

Author

Poor, H. Vincent

Author_Institution

Dept. of Electr. Eng., Princeton Univ., NJ, USA

Volume

3

fYear

34881

fDate

10-14 Jul1995

Firstpage

1675

Abstract

Predictive models for generating side information in differential encoding of data (e.g., images) sampled at high densities are considered. A model based on incremental difference operators is used in place of the conventional linear predictive coding (LPC) paradigm. It is seen that, unlike standard LPC, this formulation is stable for high sampling densities. Moreover, this formulation leads to more efficiently encoded side information in this regime

Keywords

data compression; encoding; geophysical signal processing; geophysical techniques; image coding; remote sensing; differential encoding; geophysical measurement technique; high sampling densities; high-resolution; image coding; image compression; image processing; incremental difference operator; land surface; predictive model; remote sensing; side information; terrain mapping; Data mining; Discrete cosine transforms; Electronic mail; Encoding; Image coding; Image sampling; Linear predictive coding; Predictive models; Signal processing; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International

Conference_Location

Firenze

Print_ISBN

0-7803-2567-2

Type

conf

DOI

10.1109/IGARSS.1995.523993

Filename

523993