[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5573/IEIESPC.2016.5.6.390

Sharpness-aware Evaluation Methodology for Haze-removal Processing in Automotive Systems

Hwang, Seokha (Department of Electronic Engineering, Kwangwoon University)
Lee, Youngjoo (Department of Electronic Engineering, Kwangwoon University)

Publication Information

IEIE Transactions on Smart Processing and Computing / v.5, no.6, 2016 , pp. 390-394 More about this Journal

Abstract

This paper presents a new comparison method for haze-removal algorithms in next-generation automotive systems. Compared to previous peak signal-to-noise ratio-based comparisons, which measure similarity, the proposed modulation transfer function-based method checks sharpness to select a more suitable haze-removal algorithm for lane detection. Among the practical filtering schemes used for a haze-removal algorithm, experimental results show that Gaussian filtering effectively preserves the sharpness of road images, enhancing lane detection accuracy.

Keywords

Advanced driver assistance systems; Lane detection; Haze-removal algorithm; Image comparison methodology;

Citations & Related Records

Reference

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