Structure-preserving texture filtering for adaptive image smoothing. (April 2018)

• Record Type: Journal Article
• Authors: Song, Chengfang; Xiao, Chunxia; Li, Xuefei; Li, Jing; Sui, Haigang
• Is Part Of: Journal of visual languages & computing. Volume 45(2018)
• Page Start: 17
• Page End: 23
• Publication Date: 2018-04
• Subjects: Image smoothing -- Texture filtering -- Structure measurement; Visual programming languages (Computer science) -- Periodicals; Visual programming (Computer science) -- Periodicals; Programming languages (Electronic computers) -- Semantics -- Periodicals; Langages de programmation visuelle -- Périodiques; Programmation visuelle -- Périodiques; Langages de programmation -- Sémantique -- Périodiques; Programming languages (Electronic computers) -- Semantics; Visual programming (Computer science); Visual programming languages (Computer science); Periodicals; Electronic journals; 005
• DOI: 10.1016/j.jvlc.2018.02.002
• Languages: English
• ISSNs: 1045-926X

Abstract

Abstract: Extracting meaningful structures from images with complicated texture patterns is challenging since it is hard to separate structure from texture with similar scale or intensity contrast. In this paper, we propose a structure-preserving bilateral texture filtering algorithm to smooth texture while preserving salient structures. We design a dual-scale patch toggle scheme. That is, two-scale patches are exploited to represent pixels alternatively, the smaller ones for pixels located at structure edges and the bigger ones for pixels in textural regions, and DASM (Directional Anisotropic Structure Measurement) on each pixel is estimated to select which type of patch for it. Our algorithm is based on the framework of joint bilateral filtering, so it is fast, easy to implement, yet effective for adaptive image smoothing. In particular, our approach outperforms previous methods in terms of preserving small structures. The proposed method achieves excellent results that illustrate its effectiveness and efficiency.