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Illuminant and Device Invariance Using Histogram Equalisation

机译:使用直方图均衡化的光源和设备不变性

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In this paper we propose a new device and illumination invariant image representation based on an existing grey-scale image enhancement technique: histogram equalisation. Our method is based on the premise that the rank ordering of sensor responses is preserved across a change in imaging conditions (lighting or device). We set out the theoretical conditions under which this premise is true and we present empirical evidence which demonstrates that rank ordering is maintained in practice for a wide range of il-luminants and imaging devices. We then show how we can exploit this rank invariance using histogram equalisation to derive an invariant image representation. Device and illuminant invariance are important in many imaging applications and in this paper we demonstrate the practical benefits of our new method in one such situation: the problem of image retrieval. We show that using the new invariant image representation to index into a database of images taken with a variety of devices under different lights provides very good indexing performance across all imaging conditions.
机译:在本文中,我们基于现有的灰度图像增强技术:直方图均衡化,提出了一种新的设备和照明不变图像表示。我们的方法基于以下前提:在成像条件(照明或设备)的变化中,传感器响应的等级顺序得以保留。我们提出了在此前提下成立的理论条件,并提供了经验证据,证明了在实践中,对于各种照明设备和成像设备,都可以保持等级排序。然后,我们展示了如何利用直方图均衡化来利用这种秩不变性,以得出不变的图像表示形式。设备和光源不变性在许多成像应用中都很重要,在本文中,我们演示了这种新方法在一种情况下的实际好处:图像检索问题。我们表明,使用新的不变图像表示法将不同设备在不同光照下拍摄的图像数据库建立索引,可以在所有成像条件下提供非常好的索引性能。

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