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Parametric logarithmic type image processing for contrast based auto-focus in extreme lighting conditions

机译:在极端光照条件下基于对数自动对焦的参数对数型图像处理

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While most of state-of-the-art image processing techniques were built under the so-called classical linear image processing, an alternative that presents superior behavior for specific applications comes in the form of Logarithmic Type Image Processing (LTIP). This refers to mathematical models constructed for the representation and processing of gray tones images. In this paper we describe a general mathematical framework that allows extensions of these models by various means while preserving their mathematical properties. We propose a parametric extension of LTIP models and discuss its similarities with the human visual system. The usability of the proposed extension model is verified for an application of contrast based auto-focus in extreme lighting conditions. The closing property of the named models facilitates superior behavior when compared with state-of-the-art methods.
机译:虽然大多数最新的图像处理技术都是在所谓的经典线性图像处理下构建的,但对数类型图像处理(LTIP)的形式却可以为特定应用提供出色的性能。这是指构建用于表示和处理灰度图像的数学模型。在本文中,我们描述了一个通用的数学框架,该框架允许通过各种方式扩展这些模型,同时保留其数学特性。我们提出LTIP模型的参数扩展,并讨论其与人类视觉系统的相似性。对于在极端光照条件下基于对比度的自动对焦的应用,验证了所提议扩展模型的可用性。与最先进的方法相比,命名模型的闭合特性可促进优异的行为。

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