Multiscale retinex for improved performance in multispectral image classification

Beverly J. Thompson; Zia-ur Rahman; Stephen K. Park

doi:10.1117/12.390485

29 June 2000 Multiscale retinex for improved performance in multispectral image classification

Beverly J. Thompson, Zia-ur Rahman, Stephen K. Park

Proceedings Volume 4041, Visual Information Processing IX; (2000) https://doi.org/10.1117/12.390485
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

Image preprocessing is useful in helping to identify `spectral response patterns' for certain types of image classification problems. The common artifacts in remotely sensed images are caused by the blurring due to the optics of the image gathering device, illumination variations, and the radiative transfer of the atmosphere. The Multi-Scale Retinex (MSR) image enhancement algorithm that provides dynamic range compression, reduced dependence on lighting conditions, and improved (perceived) spatial resolution has proven to be an effective tool in the correction of image degradations such as those in remote sensing images. In this paper, we measure the improvement in classification accuracy due to the application of the MSR algorithm. We use simulated images generated with different scene irradiance and with known ground truth data. The simulation results show that, despite the degree of image degradation due to changes in atmospheric irradiance, classification error can be substantially reduced by preprocessing the image data with the MSR. Furthermore we show that, similar to the results achieved in previous work, the classification results obtained from the MSR preprocessed images for various scene irradiance are more similar to each other than are the classification results for the original unprocessed images. This is evident in the observed visual quality of the MSR enhanced images even before classification is performed, and in the different images obtained by comparing image data under different irradiance conditions. We conclude that the application of the MSR algorithm results in improved visual quality and increased spatial variation of multispectral images that is also optimal for certain types of multispectral image classification.

Citation Download Citation

Beverly J. Thompson, Zia-ur Rahman, and Stephen K. Park "Multiscale retinex for improved performance in multispectral image classification", Proc. SPIE 4041, Visual Information Processing IX, (29 June 2000); https://doi.org/10.1117/12.390485

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available