A Image Enhancement Method For Night-Way Images

Year 2021, Volume: 9 Issue: 1, 8 - 16, 30.01.2021

Bülent Turan

https://doi.org/10.17694/bajece.802855

Cited By: 3

Abstract

Image processing has a wide range of applications especially in our daily lives. Image processing is not common in sensitive industrial applications. Because of these applications, very high percentage of success is requested. Also these applications work in real-time. However, it can be widely used in many daily routines (driving, entrance to the workplace/ exit, control of multimedia devices, security applications, identification applications, etc.). Especially Advanced Driver Assistance Systems (ADAS) is a popular working area for image processing. Strip tracking systems, pedestrian detection systems, reading of traffic signs and signals are based on image processing.
In this study, a new method has been developed to increase the visibility levels of road images at night driving. In these images, the brightness level is low because of insufficient of light sources (headlights and road lighting) which are often used to increase the driver's view. On the other hand, adversely affects the view of driver which the headlight of coming vehicles from opposite directions, poorly structured road lighting and etc. Especially the vehicle headlights coming from the opposite direction take the eye of the drivers and cause the level of view to decrease.
Intense dark areas and light sources are in the image together. By so, special to these images requires the use of an adaptive improvement method. This is because, when classical image enhancement methods are used, the visibility levels of the dark areas are increased, and the shining regions are more likely to shine and the visibility level decreases in these regions.
The developed method aims at enhancement these images that drivers be exposed to. For this purpose, the light sources in the image and the magnitudes of these light sources, the distance of the pixels to be calculated from the light sources, the value of the pixel itself and the neighboring pixels are used as separate parameters. Images are enhancement with the equations developed using these parameters. When the output images obtained with the use of the developed equations and the obtained Structural Similarity İndex Maps (SSIM) are examined, it is seen that the developed method gives good results.

Keywords

ADAS, early warning, image enhancement, night road images, pedestrian detection

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