Share Email Print

Proceedings Paper

Self-consistent mathematical morphological filter for removing cirrus noise from far-infrared astronomical images
Author(s): Lun X. He; John P. Basart; Philip N. Appleton; Jeffrey A. Pedelty
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The presence of diffuse far-infrared emission from the interstellar dust which has the form of the so-called 'Galactic-cirrus' has made the detection and flux determination of faint extragalactic sources difficult, especially near the Galactic plane. This effect is most serious at long infrared wavelengths around (lambda) 100 micrometers , and is especially obvious in sky survey images made with the infrared astronomical satellite (IRAS) at those wavelengths. We describe the development of a filter designed to remove the cirrus emission from the IRAS images using classification and morphological operations. The technique, based upon 'sieving', involves extracting the size information of the objects to form a growth cube, and then classifying the growth information with the K-means method. This allows the cirrus emission to be distinguished from other forms of emission in the images. The growth characteristic of the cirrus is then used to remove the cirrus components from the growth for each pixel for each field making extragalactic infrared emission more observable. This filtering process was applied to various fields detected by IRAS and the cirrus noise filtered successfully.

Paper Details

Date Published: 11 August 1995
PDF: 13 pages
Proc. SPIE 2568, Neural, Morphological, and Stochastic Methods in Image and Signal Processing, (11 August 1995); doi: 10.1117/12.216343
Show Author Affiliations
Lun X. He, Iowa State Univ. (United States)
John P. Basart, Iowa State Univ. (United States)
Philip N. Appleton, Iowa State Univ. (United States)
Jeffrey A. Pedelty, NASA Goddard Space Flight Ctr. (United States)

Published in SPIE Proceedings Vol. 2568:
Neural, Morphological, and Stochastic Methods in Image and Signal Processing
Edward R. Dougherty; Francoise J. Preteux; Sylvia S. Shen, Editor(s)

© SPIE. Terms of Use
Back to Top