| 乔景慧,苏冠赫,闫书源.三分量双色反射模型驱动的透明PET瓶图像高光去除方法研究[J].电子测量与仪器学报,2025,39(2):92-101 |
| 三分量双色反射模型驱动的透明PET瓶图像高光去除方法研究 |
| Research on highlight removal method driven by three component dichromaticreflection model for transparent PET bottle images |
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| DOI： |
| 中文关键词: 透明PET瓶 双色反射模型 高光去除 图像修复 L2归一化色度 |
| 英文关键词:transparent PET bottle dichromatic reflection model highlight removal image restoration L2 normalized chromaticity |
| 基金项目:辽宁省教育厅面上基金(LJ212410142020)、辽宁省研究生教育教学改革研究（LNYJG2022073）、沈阳工业大学研究生教育教学改革研究项目（SYJG20222002）、沈阳工业大学重点科研基金（ZDZRGD2020004）项目资助 |
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| 摘要点击次数: 16 |
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| 中文摘要: |
| 光照射条件下物体表面产生的高光造成物体自身颜色信息丢失，影响立体匹配、三维重建中特征提取的质量。针对含有漫反射量和镜面反射量的双色反射模型无法准确描述透明PET瓶反射量的成分分布，提出基于L2归一化三分量双色反射模型的高光去除方法。首先对透明PET图像构建L2归一化三分量双色反射模型，阐明透明PET瓶反射量成分分布机理；再依据此模型将透明PET图像全局像素信息进行分解，计算L2归一化色度图；在此基础上依据L2归一化色度图计算全局像素的L2色度强度比；其次对指数变换L2归一化色度图聚类分析，检测透明PET瓶的高光区域并捕捉PET瓶自身颜色信息；最后结合L2色度强度比实现高光区域的像素信息恢复。实验部分建立了透明PET瓶数据集并进行验证，实验结果表明，与传统双色反射模型驱动的高光去除方法相比，所提出方法在均方误差(MSE)、峰值信噪比(PSNR)及结构相似性(SSIM)分别提高了12.1%、21.1%、11.5%。 |
| 英文摘要: |
| The highlight generated on the surface of an object under light irradiation conditions causes the loss of its own color information, which affects the quality of feature extraction in stereo matching and 3D reconstruction. Aiming at the phenomenon that the dichromatic reflection model containing diffuse reflection and specular reflection cannot accurately describe the component distribution of reflection in transparent PET bottles, a highlight removal method based on L2 normalized three component dichromatic reflection model is proposed. Firstly, a L2 normalized three component dichromatic reflection model is constructed for transparent PET images to elucidate the distribution of reflectance components in transparent PET bottles. Based on this model, decompose the global pixel information of the transparent PET image and calculate the L2 normalized chromaticity map; On this basis, calculate the L2 chromaticity intensity ratio of global pixels based on the L2 normalized chromaticity diagram. Next, perform clustering analysis on the L2 normalized chromaticity diagram using exponential transformation to detect the highlight areas of transparent PET bottles and capture the inherent color information of the PET bottles. Finally, combining L2 chromaticity intensity ratio to achieve pixel information recovery in highlight areas. The experimental part established a transparent PET bottle dataset and validated it. The experimental results showed that compared with the traditional dichromatic reflection model driven highlight removal method, the proposed method improved the mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) indicators by 12.1%, 21.1%, and 11.5%, respectively. |
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