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Comparative Study on Illumination Compensation Performance of Retinex model and Illumination-Reflectance model  

Chung, Jin-Yun (한국과학기술원 전자전산학과)
Yang, Hyun-Seung (한국과학기술원 전자전산학과)
Publication Information
Journal of KIISE:Software and Applications / v.33, no.11, 2006 , pp. 936-941 More about this Journal
Abstract
To apply object recognition techniques to real environment, illumination compensation method should be developed. As effective illumination compensation model, we focused our attention on Retinex model and illumination-Reflectance model, implemented them, and experimented on their performance. We implemented Retinex model with Single Scale Retinex, Multi-Scale Retinex, and Retinex Neural Network and Multi-Scale Retinex Neural Network, neural network model of Retinex model. Also, we implemented illumination-Reflectance model with reflectance image calculation by calculating an illumination image by low frequency filtering in frequency domain of Discrete Cosine Transform and Wavelet Transform, and Gaussian blurring. We compare their illumination compensation performance to facial images under nine illumination directions. We also compare their performance after post processing using Principal Component Analysis(PCA). As a result, illumination Reflectance model showed better performance and their overall performance was improved when illumination compensated images were post processed by PCA.
Keywords
Illumination compensation; Retinex model; Illumination-reflectance model;
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