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A novel illumination compensation method using wavelet packet transformation

机译:一种新的使用小波包变换的照明补偿方法

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A novel illumination compensate method is proposed in this paper to improve recognition performance. A modified lighting model called Lambertin which includes additive noise and multiplicative noise are presented firstly. Then, additive noise is removed by using wavelet packet transformation. Next, the processed image is transformed into logarithm domain and the multiplicative noise, which has been named additive noise, is removed by means of the same above algorithm. Finally, a compensated face image is obtained. We examine the proposed method on Yale extended B database compared with other methods. Experimental results show that our algorithm improves by 3%~12% recognition rate. It can effectively adjust the facial images for varying illumination conditions and also improve the recognition performance and robustness.
机译:本文提出了一种新的照明补偿方法,以提高识别性能。首先介绍了包括添加剂噪声和乘法噪声的兰伯特汀的改进的照明模型。然后,通过使用小波包变换去除附加噪声。接下来,将处理的图像转换为对数域,并且通过相同的上述算法通过相同的算法去除已经命名的附加噪声的乘法噪声。最后,获得补偿面图像。与其他方法相比,我们检查了耶鲁扩展B数据库的提出方法。实验结果表明,我们的算法提高了3%〜12%的识别率。它可以有效地调整面部图像以进行不同的照明条件,并提高识别性能和鲁棒性。

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