本征图像分解的可变尺度局部分析与集成方法

doi:10.16451/j.cnki.issn1003-6059.202104004

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Abstract A unified mathematical model and an algorithm are proposed to solve the problems of the estimation of illumination and reflectance images of a natural image and the segmentation and bias field estimation of a magnetic resonance image(MRI). The proposed model only requires a basic assumption that the observed image can be approximated by the product of two intrinsic images with different properties. One of the two intrinsic images is a smooth image, S-image, and the other is a piece-wise approximately constant image, L-image. To fully exploit the properties of the intrinsic images, a scalable local analysis and integration(SLAI) approach is proposed for the problem of intrinsic image estimation. Due to the smoothness of the S-image, a low order Taylor expansion or a linear combination of general smooth basis functions is utilized to locally approximate the S-image. The obtained local smooth approximation of the S-image can be extended to a smooth image on the entire region of interest(ROI) using partition of unity subordinate to a cover of ROI. Meanwhile, the segmentation result and the estimation of the L-image are obtained. The proposed method is based on a weaker assumption than the methods in the literature, and therefore it is applicable to more images. The proposed method produces satisfactory results on MR images and natural images.

Key words： Intrinsic Image Image Segmentation Illumination and Reflectance Image Magnetic Resonance Imaging

Received: 09 July 2020

ZTFLH:

TP 391.41

Fund:National Natural Science of Foundation of China(No.G0561671135)

Corresponding Authors: LI Chunming, Ph.D., professor. His research interests include computer vision and medical image analysis.

About author:: SHI Xue, Ph.D. candidate. Her research interests include image processing and medical image analysis. XU Haiping, Ph.D., lecturer. Her research interests include image processing and machine learning.

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Cite this article:

SHI Xue,XU Haiping,LI Chunming. A Scalable Local Analysis and Integration Approach to Intrinsic Image Decomposition[J]. , 2021, 34(4): 322-332.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202104004 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2021/V34/I4/322

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