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对数图像处理框架中利用负灰度级实现图像增强

Image Enhancement Thanks to Negative Grey Levels in the Logarithmic Image Processing Framework.

作者信息

Jourlin Michel

机构信息

Laboratoire Hubert Curien, UMR CNRS 5516, 18 Rue Professeur Benoît Lauras, 42000 Saint-Étienne, France.

出版信息

Sensors (Basel). 2024 Jul 31;24(15):4969. doi: 10.3390/s24154969.

DOI:10.3390/s24154969
PMID:39124018
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11314874/
Abstract

The present study deals with image enhancement, which is a very common problem in image processing. This issue has been addressed in multiple works with different methods, most with the sole purpose of improving the perceived quality. Our goal is to propose an approach with a strong physical justification that can model the human visual system. This is why the Logarithmic Image Processing (LIP) framework was chosen. Within this model, initially dedicated to images acquired in transmission, it is possible to introduce the novel concept of negative grey levels, interpreted as light intensifiers. Such an approach permits the extension of the dynamic range of a low-light image to the full grey scale in "real-time", which means at camera speed. In addition, this method is easily generalizable to colour images and is reversible, i.e., bijective in the mathematical sense, and can be applied to images acquired in reflection thanks to the consistency of the LIP framework with human vision. Various application examples are presented, as well as prospects for extending this work.

摘要

本研究涉及图像增强，这是图像处理中一个非常常见的问题。在多项研究中已采用不同方法解决了这个问题，大多数方法的唯一目的是提高感知质量。我们的目标是提出一种具有充分物理依据的方法，该方法能够模拟人类视觉系统。这就是选择对数图像处理（LIP）框架的原因。在这个最初专门用于透射采集图像的模型中，可以引入负灰度级的新概念，将其解释为光增强器。这种方法允许将低光图像的动态范围“实时”扩展到全灰度级，即相机速度。此外，该方法很容易推广到彩色图像，并且是可逆的，即在数学意义上是双射的，并且由于LIP框架与人类视觉的一致性，可以应用于反射采集的图像。文中给出了各种应用示例以及扩展这项工作的前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab62/11314874/8f5524bb81e7/sensors-24-04969-g015a.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab62/11314874/057b9b9e8bfa/sensors-24-04969-g010.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab62/11314874/55d959ffb223/sensors-24-04969-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab62/11314874/1cc10fa78904/sensors-24-04969-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab62/11314874/7fec42996745/sensors-24-04969-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab62/11314874/5332da06bb1b/sensors-24-04969-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab62/11314874/057b9b9e8bfa/sensors-24-04969-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab62/11314874/28cb40b0f4e9/sensors-24-04969-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab62/11314874/82e4486cc1d6/sensors-24-04969-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab62/11314874/8f5524bb81e7/sensors-24-04969-g015a.jpg

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