Infrared/visible image feature domain fusion algorithm

Abstract In Multi-scale Geometric Analysis (MGA)-based fusion methods for infrared and visible images, adopting the same representation for the two types of the images will result in the non-obvious thermal radiation target in the fused image, which can hardly be distinguished from the background. To solve the problem, a novel fusion algorithm based on nonlinear enhancement and Non-Subsampled Shearlet Transform (NSST) decomposition is proposed. Firstly, NSST is used to decompose the two source images into low- and high-frequency sub-bands. Then, the Wavelet Transform (WT) is used to decompose high-frequency sub-bands into obtain approximate sub-bands and directional detail sub-bands. The “average” fusion rule is performed for fusion for approximate sub-bands. And the “max-absolute” fusion rule is performed for fusion for directional detail sub-bands. The inverse WT is used to reconstruct the high-frequency sub-bands. To highlight the thermal radiation target, we construct a non-linear transform function to determine the fusion weight of low-frequency sub-bands, and whose parameters can be further adjusted to meet different fusion requirements. Finally, the inverse NSST is used to reconstruct the fused image. The experimental results show that the proposed method can simultaneously enhance the thermal target in infrared images and preserve the texture details in visible images, and which is competitive with or even superior to the state-of-the-art fusion methods in terms of both visual and quantitative evaluations.

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Light field camera all-in-focus image acquisition based on angular information

Optica Applicata ◽

10.37190/oa210212 ◽

2021 ◽

Vol 51 (2) ◽

Author(s):

Yingchun Wu, , , , ◽

Xing Cheng ◽

Jie Liang ◽

Anhong Wang ◽

Xianling Zhao

Keyword(s):

Image Fusion ◽

Field Data ◽

Light Field ◽

Spatial Information ◽

Human Perception ◽

Energy Difference ◽

Image Feature ◽

Fusion Algorithm ◽

Fused Image ◽

Focus Image

Traditional light field all-in-focus image fusion algorithms are based on the digital refocusing technique. Multi-focused images converted from one single light field image are used to calculate the all-in-focus image and the light field spatial information is used to accomplish the sharpness evaluation. Analyzing the 4D light field from another perspective, an all-in-focus image fusion algorithm based on angular information is presented in this paper. In the proposed method, the 4D light field data are fused directly and a macro-pixel energy difference function based on angular information is established to accomplish the sharpness evaluation. Then the fused 4D data is guided by the dimension increased central sub-aperture image to obtain the refined 4D data. Finally, the all-in-focus image is calculated by integrating the refined 4D light field data. Experimental results show that the fused images calculated by the proposed method have higher visual quality. Quantitative evaluation results also demonstrate the performance of the proposed algorithm. With the light field angular information, the image feature-based index and human perception inspired index of the fused image are improved.

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Image Feature Analysis and Dynamic Measurement of Plantar Pressure Based on Fusion Feature Extraction

Traitement du signal ◽

10.18280/ts.380627 ◽

2021 ◽

Vol 38 (6) ◽

pp. 1829-1835

Author(s):

Ji Zou ◽

Chao Zhang ◽

Zhongjing Ma ◽

Lei Yu ◽

Kaiwen Sun ◽

...

Keyword(s):

Feature Extraction ◽

Plantar Pressure ◽

Dynamic Measurement ◽

Image Features ◽

Image Feature ◽

Feature Analysis ◽

Fusion Algorithm ◽

Massive Datasets ◽

Processing Power ◽

Fusion Feature

Footprint recognition and parameter measurement are widely used in fields like medicine, sports, and criminal investigation. Some results have been achieved in the analysis of plantar pressure image features based on image processing. But the common algorithms of image feature extraction often depend on computer processing power and massive datasets. Focusing on the auxiliary diagnosis and treatment of foot rehabilitation of foot laceration patients, this paper explores the image feature analysis and dynamic measurement of plantar pressure based on fusion feature extraction. Firstly, the authors detailed the idea of extracting image features with a fusion algorithm, which integrates wavelet transform and histogram of oriented gradients (HOG) descriptor. Next, the plantar parameters were calculated based on plantar pressure images, and the measurement steps of plantar parameters were given. Finally, the feature extraction effect of the proposed algorithm was verified, and the measured results on plantar parameters were obtained through experiments.

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Infrared and Visible Image Fusion Based on Nonlinear Enhancement and NSST Decomposition

10.21203/rs.2.24788/v1 ◽

2020 ◽

Author(s):

Xiaoxue XING ◽

Cheng LIU ◽

Cong LUO ◽

Tingfa XU

Keyword(s):

Thermal Radiation ◽

High Frequency ◽

Geometric Analysis ◽

Low Frequency ◽

Fusion Rule ◽

Fusion Algorithm ◽

Visible Image ◽

Fused Image ◽

Fusion Methods ◽

Visible Images

Abstract In Multi-scale Geometric Analysis (MGA)-based fusion methods for infrared and visible images, adopting the same representation for the two types of the images will result in the non-obvious thermal radiation target in the fused image, which can hardly be distinguished from the background. To solve the problem, a novel fusion algorithm based on nonlinear enhancement and Non-Subsampled Shearlet Transform (NSST) decomposition is proposed. Firstly, NSST is used to decompose the two source images into low- and high-frequency sub-bands. Then, the wavelet transform(WT) is used to decompose high-frequency sub-bands into obtain approximate sub-bands and directional detail sub-bands. The “average” fusion rule is performed for fusion for approximate sub-bands. And the “max-absolute” fusion rule is performed for fusion for directional detail sub-bands. The inverse WT is used to reconstruct the high-frequency sub-bands. To highlight the thermal radiation target, we construct a non-linear transform function to determine the fusion weight of low-frequency sub-bands, and whose parameters can be further adjusted to meet different fusion requirements. Finally, the inverse NSST is used to reconstruct the fused image. The experimental results show that the proposed method can simultaneously enhance the thermal target in infrared images and preserve the texture details in visible images, and which is competitive with or even superior to the state-of-the-art fusion methods in terms of both visual and quantitative evaluations.

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