Document Type

Thesis - University Access Only

Award Date


Degree Name

Master of Science (MS)

Department / School

Electrical Engineering


A new algorithm for coherent noise (CN) characterization and correction on the ETM+ was created. The thought behind this new algorithm is to improve the Image Assessment System (IAS). Characterizing the magnitude and phase spectrum of CN for Landsat 7 imagery is done by using periodogram spectral estimation via the fast Fourier transform (FFT) . Characterization is divided into an image group and a calibration group. Each group contains multiple bands, detectors, and scan directions. The CN component is characterized by the following properties: amplitude, frequency, phase, width, height, and resolution. A relationship between the estimated phase and magnitude of CN components at the Nyquist frequency is determined. A high estimated phase error would be encountered if the estimated CN magnitude is low, and vice versa. The sensitivity for CN characterization algorithm is as low as 0.01 Digital Number (DN). CN correction methods are developed for band 8 at the Nyquist frequency. Two correction algorithms are presented. They are the spatial algorithm and the Fourier transform algorithm. The Fourier transform algorithm has more advantages than the spatial algorithm.

Library of Congress Subject Headings

Landsat satellites -- Noise Landsat satellites -- Calibration Imaging systems -- Image quality



Number of Pages



South Dakota State University