A new approach to estimate image blur extent based on wavelet module maximum

Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently.

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Make Your Picture More Attractive – An Interactive System for Image Blur

Wang¹

2012

IJCCE

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A new approach to estimate image blur extent based on wavelet module maximum

Cited by 3 publications

References 8 publications

Image Deblurring Using Fast Best Kernel Retrieval

Image Deblurring Using Fast Best Kernel Retrieval

Restoration of Motion-Blurred Image Based on Border Deformation Detection: A Traffic Sign Restoration Model

Make Your Picture More Attractive – An Interactive System for Image Blur

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