标题：Traffic Sign Image Denoising with Energy-based Adaptive Finite Ridgelet Transform
作者：Liu Yunxia; Tian Guohui; Yang Yang; Zhou Fengyu
作者机构：[Liu Yunxia; Tian Guohui; Yang Yang; Zhou Fengyu] Shandong Univ, Sch Control Sci & Engn, Jinan 250014, Peoples R China.
会议名称：32nd Chinese Control Conference (CCC)
会议日期：JUL 26-28, 2013
来源：2013 32ND CHINESE CONTROL CONFERENCE (CCC)
关键词：intelligent transportation system; image denoising; wavelet transform;; finite ridgelet transform
摘要：Denoising of traffic sign images is an important pre-processing step in intelligent transportation system whose performance greatly affects subsequent manipulations. Based on characteristic analysis of traffic sign images that linear singularities is more informative, this paper introduced the finite ridgelet transform (FRIT) for traffic sign image denoising. An energy based adaptive finite ridgelet transform scheme (EFRIT) is proposed for better presentation of linear singularities. Abundant experimental results carried out on different types of traffic sign images at varying noise levels demonstrate the effectiveness of the proposed algorithm in both terms of PSNR and visual quality.