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Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators.

Bai X - Sensors (Basel) (2015)

Bottom Line: Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed.Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features.All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion.

View Article: PubMed Central - PubMed

Affiliation: Image Processing Center, Beijing University of Aeronautics and Astronautics, Beijing 100191, China. jackybxz@buaa.edu.cn.

ABSTRACT
The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion.

No MeSH data available.


Related in: MedlinePlus

An example on Navi images. (a) Original infrared image (b) Original visual image (c) Result of MSTHT; (d) Result of SIDWT (e) Result of LP (f) Result of MSTHST; (g) Result of MSNTHT (h) Result of MSTOOC (i) Result of the proposed algorithm.
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sensors-15-17149-f003: An example on Navi images. (a) Original infrared image (b) Original visual image (c) Result of MSTHT; (d) Result of SIDWT (e) Result of LP (f) Result of MSTHST; (g) Result of MSNTHT (h) Result of MSTOOC (i) Result of the proposed algorithm.

Mentions: Figure 3 is an example of infrared and visual image fusion performed on the Navi images. The details in the original images are not clear. It would be important to produce a clear fusion result with rich details. The details of the result of MSTHT are not clear, thus the fusion result is unclear. The result of MSNTHT is better than MSTHT, but the image details are still not clear. The details of the results of SIDWT, LP and MSTHST are clearer than MSTHT and MSNTHT, but the details in the result of MSTOOC are clearer than SIDWT, LP and MSTHST. Moreover, among these algorithms, the result of the proposed algorithm is the clearest and the details are very rich, which indicates its effective performance for infrared and visual image fusion. This would be very useful for the further image analysis.


Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators.

Bai X - Sensors (Basel) (2015)

An example on Navi images. (a) Original infrared image (b) Original visual image (c) Result of MSTHT; (d) Result of SIDWT (e) Result of LP (f) Result of MSTHST; (g) Result of MSNTHT (h) Result of MSTOOC (i) Result of the proposed algorithm.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541927&req=5

sensors-15-17149-f003: An example on Navi images. (a) Original infrared image (b) Original visual image (c) Result of MSTHT; (d) Result of SIDWT (e) Result of LP (f) Result of MSTHST; (g) Result of MSNTHT (h) Result of MSTOOC (i) Result of the proposed algorithm.
Mentions: Figure 3 is an example of infrared and visual image fusion performed on the Navi images. The details in the original images are not clear. It would be important to produce a clear fusion result with rich details. The details of the result of MSTHT are not clear, thus the fusion result is unclear. The result of MSNTHT is better than MSTHT, but the image details are still not clear. The details of the results of SIDWT, LP and MSTHST are clearer than MSTHT and MSNTHT, but the details in the result of MSTOOC are clearer than SIDWT, LP and MSTHST. Moreover, among these algorithms, the result of the proposed algorithm is the clearest and the details are very rich, which indicates its effective performance for infrared and visual image fusion. This would be very useful for the further image analysis.

Bottom Line: Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed.Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features.All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion.

View Article: PubMed Central - PubMed

Affiliation: Image Processing Center, Beijing University of Aeronautics and Astronautics, Beijing 100191, China. jackybxz@buaa.edu.cn.

ABSTRACT
The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion.

No MeSH data available.


Related in: MedlinePlus