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

C. Florea, L. Florea
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引用次数: 14

Abstract

Abstract 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.
参数对数型图像处理在极端光照条件下基于对比度的自动对焦
虽然大多数最先进的图像处理技术都是在所谓的经典线性图像处理下建立的,但对数类型图像处理(LTIP)的形式为特定应用提供了更好的行为。这是指为表示和处理灰度图像而构建的数学模型。在本文中,我们描述了一个通用的数学框架,允许通过各种方式扩展这些模型,同时保持它们的数学性质。我们提出了LTIP模型的参数化扩展,并讨论了其与人类视觉系统的相似性。在极端光照条件下基于对比度的自动对焦应用中验证了所提出的扩展模型的可用性。与最先进的方法相比,命名模型的关闭属性促进了更好的行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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