ICTACT Journal on Image and Video Processing

K. Kannan ¹, S. Arumuga Perumal ²

Affiliations
1 Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, IN
2 Department of Computer Science, S.T. Hindu College, IN

Abstract

Image fusion is the process of combining two or more images of the same scene to form the fused image retaining important features from each image with extended information content. There are two approaches to image fusion, namely Spatial Fusion and Transform fusion. Transform fusion uses transform for representing the source image at multi scale. Due to the compactness, orthogonality and directional information, the Discrete Wavelet Transforms and its undecimated version are used for image fusion. These transforms can be implemented using perfect reconstruction Finite Impulse Response filter banks which are either symmetric or orthogonal. To design filters to have both symmetric and orthogonal properties, the number of filters is increased to generate M-band transform. Double density Discrete Wavelet Transform is an example of M-band DWT and consists of one scaling and two wavelet filters. In this paper, an approach for DDWT based image fusion is designed using statistical property of wavelet filters in representing the sharpness and its performance is measured in terms of Root Mean Square Error, Peak to Signal Noise Ratio, Quality Index.

Keywords

Image Fusion, Discrete Wavelet Transform (DWT), Finite Impulse Response Filter, M-Band Transform and Double Density Discrete Wavelet Transform (DDWT).

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K. Kannan ¹, S. Arumuga Perumal ²

Affiliations
1 Kamaraj College of Engineering and Technology, Tamil Nadu, IN
2 S.T. Hindu College, Tamil Nadu, IN

Abstract

In machine vision, due to the limited depth-of-focus of optical lenses in CCD devices, it is not possible to have a single image that contains all the information of objects in the image. To achieve this, image fusion is required which is usually refers to the process of combining two or more different images, each containing different features into a new single image retaining important features from each and every image with extended information content. The approaches to image fusion can be classified into two namely Spatial Fusion and Transform fusion. The most commonly used transform for image fusion at multi scale is Discrete Wavelet Transform since it minimizes structural distortions. But, wavelet transform suffers from lack of shift invariance and this disadvantage is overcome by Stationary Wavelet Transform. This paper describes the optimum level of decomposition of Stationary Wavelet Transform for region based fusion of multi focused images in terms of various performance measures.

Keywords

Image Fusion, Region Level Fusion, Discrete Wavelet Transform and Stationary Wavelet Transform.

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