为减少水下视觉系统的蓝绿色照明,对Lab颜色模型进行了修改

A. A. Ghani, A. Nasir, Muhammad Aizzat Bin Zakaria, A. N. Ibrahim
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引用次数: 4

摘要

深海图像受到低对比度和蓝绿色照明的影响,导致物体的可见性受到限制。以往提出的用于水下视觉系统的增强技术大多提高了图像对比度,但在图像中保留了蓝绿色照明。本文讨论了在Lab色彩模型修正中利用浓度提高水下图像对比度的方法。该颜色模型中的Lab颜色元素的修改是基于将图像的整个像素移动到另一个移位值,其中新的移位值在图像对比度方面有所提高,并且基于图像中的最优信息最小化了蓝绿照明。该方法集成了两个主要步骤:暗拉伸图像融合(DSF)和像素分布移位(PDS)。在DSF步骤中,暗通道图像被拉伸,分成两个通道,然后融合在一起。其次,将Lab颜色模型中的图像像素分布向基于人类视觉系统的更自然的视图偏移。定性评价表明,在输出图像的图像对比度显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modification of Lab color model for minimizing blue-green illumination of underwater vision system
Deep underwater images suffer from low contrast and blue-green illumination which leads towards restriction to the visibility of the objects. Most of the previous proposed enhancement techniques for underwater vision system applications improve the image contrast but blue-green illumination retains in the images. This paper discusses the improvement of underwater image contrast with concentration in modification of Lab color model. The modification of Lab color element in this color model based on shifting the entire pixels of the image to another shifting values, in which, the new shifted values exhibit an improvement in terms of image contrast and minimizing blue-green illumination based on optimal information in the image. The proposed method integrates two main steps, namely dark-stretched image fusion (DSF) and pixel distribution shifting (PDS). In DSF step, dark channel image is stretched, divided into two channels before it is fused together. Next, the image pixel distribution in Lab color model is shifted towards more natural view based on human visual system. Qualitative evaluation indicates a significant improvement of image contrast in output images.
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