۱٫ Introduction

۲٫ Enhancement Algorithm

۳٫ Experimental Results

۴٫ Conclusion

References

In order to improve the contrast and sharpness of traffic sign images obtained under low light natural environment, we propose an improved enhancement method based on discrete wavelet transform to improve image contrast. We convert the original RGB image to the HSV color space, and use the discrete wavelet transform (DWT) to decompose the luminance component (V). In the low-frequency component use multi-scale Retinex algorithm estimate the illuminance to enhance the contrast of images, the high-frequency component enhances the detail information through the multi-scale detail boosting method. Finally, adjust the saturation component (S) by a piecewise exponential transformation method to make the image color more suitable for human observation. Experimental results demonstrate that our method can better display image details while reducing the halo effect, and effectively improve the contrast and sharpness of low-light images compared with existing algorithms through subjective and objective analysis.

Introduction

As an important part of the Advanced Driver Assistance System (ADAS), Traffic Sign Recognition (TSR) can recognize the traffic sign information in real time and provide it to the driver, thus reducing driver’s driving pressure, effectively ensuring driving safety, and avoiding traffic accidents [1]. However, the traffic sign images collected by the in-vehicle devices under low illumination conditions generally have problems such as a decrease in global contrast, content blurring, or loss of details [2]. This phenomenon has an adverse effect on the subsequent detection and recognition of traffic signs, Therefore, how to enhance the visual effect of traffic sign images under low light environment and highlight useful information of images has become an urgent problem to be solved.