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DOI will be assigned to every published paper at no additional charge. πŸ“’ Call for Papers β€” Volume 13, Issue 10 (October 2026) | Submission Deadline: October 26, 2026 | Rapid peer review: 2–3 days | Impact Factor: 7.37 (SJIF 2026)

Paper Details

📄 IJAERD-OJS-0630

AN IMAGE FUSION USING WAVELET AND CURVELET TRANSFORMS

Author(s):Bhagyashri N. Kumbhar, Prof. Yogita Chaudhari
Institution:Electronics and Telecommunication(VLSI and Embedded System),G. S. Moze College Of engineering Balewadi, Pune, India
Published In:Vol. 2, Issue 4 β€” April 2015
Page No.:466-472
Domain:Engineering
Type:Research Paper
ISSN (Online):2348-4470
ISSN (Print):2348-6406
Abstract

This Image fusion is a data fusion technology which keeps images as main research contents. It refers to thetechniques that integrate multi-images of the same scene from multiple image sensor data or integrate multi images of thesame scene at different times from one image sensor. The image fusion algorithm based on Wavelet Transform which fasterdeveloped was a multi-resolution analysis image fusion method in recent decade. Wavelet Transform has good time-frequencycharacteristics. It was applied successfully in image processing field. Nevertheless, its excellent characteristic in onedimension can’t be extended to two dimensions or multi-dimension simply. Separable wavelet which was spanning by onedimensional wavelet has limited directivity. This paper introduces the Curvelet Transform and uses it to fuse images. Theexperiments show that the method could extract useful information from source images to fused images so that clear imagesare obtained. In this paper we put forward an image fusion algorithm based on Wavelet Transform and the CurveletTransform. Low and high frequency coefficients are choosen according to different frequency domain after Wavelet and theCurvelet Transform. In choosing the low-frequency coefficients, the concept of local area variance was chosen to measuringcriteria. In choosing the high frequency coefficients, the window property and local characteristics of pixels were analyzed.Finally, the proposed algorithm in this article was applied to experiments of multi-focus image fusion and complementaryimage fusion.

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🕮 How to Cite

Bhagyashri N. Kumbhar, Prof. Yogita Chaudhari, “AN IMAGE FUSION USING WAVELET AND CURVELET TRANSFORMS”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 2, Issue 4, pp. 466-472, April 2015.

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