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Proceedings Paper

A novel spatial-frequency filtering scheme for x-ray angiograms with simultaneous denoising and enhancement
Author(s): Zhenghua Huang; Liang Chen; Hao Fang; Tianxu Zhang
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Paper Abstract

X-ray angiograms, which suffer from low-contrast and noise, need to be improved by both the image enhancement and denoising techniques. However, the goals of these two tasks usually conflict, which makes it difficult to efficiently combine the enhancement and denoising in one scheme. To solve this problem, we propose a novel spatial-frequency filtering (SFF) scheme to simultaneously enhance and denoise low-quality X-ray cardiovascular angiogram images. The proposed scheme includes three key components: Firstly, a relative total variation method is employed as a guide filter to separate an input image into two parts, including the base layer with strong structures and the detail layer with weak structures and noise. Then the base layer is enhanced by a proposed improved histogram equalization (IHE) method while the detail layer is extracted by a short-time Fourier transform and is further enhanced by using a proposed adaptive correction parameter. Finally, the improved image is the combination of results obtained by the two components. Both quantitative and qualitative results of experiments on real-world low-quality X-ray angiogram images demonstrate that the proposed method outperforms the state-of-the-arts in terms of contrast enhancement, structure preservation, and noise reduction.

Paper Details

Date Published: 14 February 2020
PDF: 6 pages
Proc. SPIE 11431, MIPPR 2019: Parallel Processing of Images and Optimization Techniques; and Medical Imaging, 114310C (14 February 2020); doi: 10.1117/12.2538950
Show Author Affiliations
Zhenghua Huang, Wuhan Institute of Technology (China)
Liang Chen, Wuhan EasyDiagnosis BioMedicine Co., Ltd. (China)
Hao Fang, Wuhan Donghu Univ. (China)
Tianxu Zhang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 11431:
MIPPR 2019: Parallel Processing of Images and Optimization Techniques; and Medical Imaging
Hong Sun; Bruce Hirsch; Chao Cai, Editor(s)

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