Estimation of noise component in satellite images and its application

Author

Iikura, Yoshikazu

Author_Institution

Dept. of Comput. & Inf. Sci., Iwate Univ., Morioka, Japan

Volume

1

fYear

34881

fDate

10-14 Jul1995

Firstpage

102

Abstract

The median filter is known to be effective to estimate the amount of noise present in the image. The authors investigate its performance quantitatively, and it is compared with the Laplacian filter and the trimmed mean filter. The estimated variances are adjusted to give an unbiased estimate under ideal conditions with no structure in the image. It is also shown that the trimmed mean filter as well as the median filter are robust to simple line edge structures. The author also discusses the estimation of the covariance matrix of the noise component with interband correlation, which is useful in many algorithms for image processing, such as edge detection, data compression, and image enhancement

Keywords

correlation methods; covariance matrices; data compression; edge detection; geophysical signal processing; image coding; image enhancement; interference (signal); median filters; remote sensing; Laplacian filter; covariance matrix; data compression; edge detection; estimated variances; image enhancement; image processing; interband correlation; line edge structures; median filter; noise component; performance; satellite images; trimmed mean filter; Application software; Covariance matrix; Filters; Image edge detection; Image generation; Image processing; Laplace equations; Pixel; Satellites; Signal to noise ratio;

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.1995.519660

Filename

519660