Literature DB >> 19424394

Simple and efficient method for specularity removal in an image.

Hui-Liang Shen1, Qing-Yuan Cai.   

Abstract

For dielectric inhomogeneous objects, the perceived reflections are the linear combinations of diffuse and specular reflection components. Specular reflection plays an important role in the fields of image analysis, pattern recognition, and scene synthesis. Several methods for the separation of the diffuse and the specular reflection components have been presented based on image segmentation or local interaction of neighboring pixels. We propose a simple and effective method for specularity removal in a single image on the level of each individual pixel. The chromaticity of diffuse reflection is approximately estimated by employing the concept of modified specular-free image, and the specular component is adjusted according to the criterion of smooth color transition along the boundary of diffuse and specular regions. Experimental results indicate that the proposed method is promising when compared with other state-of-the-art techniques, in both separation accuracy and running speed.

Year:  2009        PMID: 19424394     DOI: 10.1364/ao.48.002711

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  3 in total

1.  Photometric Stereo-Based Defect Detection System for Steel Components Manufacturing Using a Deep Segmentation Network.

Authors:  Fátima A Saiz; Iñigo Barandiaran; Ander Arbelaiz; Manuel Graña
Journal:  Sensors (Basel)       Date:  2022-01-24       Impact factor: 3.576

2.  SpecSeg Network for Specular Highlight Detection and Segmentation in Real-World Images.

Authors:  Atif Anwer; Samia Ainouz; Mohamad Naufal Mohamad Saad; Syed Saad Azhar Ali; Fabrice Meriaudeau
Journal:  Sensors (Basel)       Date:  2022-08-30       Impact factor: 3.847

3.  Light Field Imaging Based Accurate Image Specular Highlight Removal.

Authors:  Haoqian Wang; Chenxue Xu; Xingzheng Wang; Yongbing Zhang; Bo Peng
Journal:  PLoS One       Date:  2016-06-02       Impact factor: 3.240

  3 in total

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