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Corresponding Author

Moustafa, Hossam El-Din

Subject Area

Electronics and Communication Engineering

Article Type

Original Study

Abstract

Curvelet transform is a recently-developed multi-scale transform, which is more suitable for objects with curves. Applications of the Curvelet transform have increased rapidly in the field of image fusion. Image fusion means the combination of two images into a single image that has the maximum information content without producing details that are non-existent in the given images. In the present work an algorithm for multi-focus color image fusion based on the Curvelet transform is implemented, analyzed, and compared with a Wavelet-based fusion algorithm. Two models for color image fusion are presented. The first is based on the RGB components of the color image, while the other is based on the YIQ color model. The quality of the fused color image is evaluated by entropy and a human perception inspired quality metric. Experimental results have shown that the Curvelet based image fusion algorithm provides a slightly better fused image than the Wavelet algorithm. In addition, the fused image has a higher value of entropy and is more accord with the human visual system.

Keywords

image fusion; Multi-focus Images - Wavelet Transform; Curvelet transform

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