[Dara, 2(9): September, 2013] ISSN: 2277-9655 Impact Factor: 1.852 http: // www.ijesrt.com (C) International Journal of Engineering Sciences & Research Technology [2284-2288] IJESRT INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY Noval Wavelet Coefficient for Fusion of Multi Modality Images and Preserving Edge Features in Medical Applications Sampath Kumar Dara *1 , Kaparthi Uday 2 *1,2 Associate Professor, Department of Electronics and Communication Engineering, Vaageswari College of Engineering, Karimnagar, Andhra Pradesh. 505481, India darasampathkumar@gmail.com Abstract Most of previous image fusion methods aim at obtaining as many as information from the different modality images. The fusion criterion is to minimize different error between the fused image and the input images. With respect to the medical diagnosis, the edges and outlines of the interested objects is more important than other information. Therefore, how to preserve the edge-like features is worthy of investigating for medical image fusion. As we know, the image with higher contrast contain more edge-like features. In term of this view, we proposed a novel medical image fusion scheme based on an improved wavelet coefficient contrast, which is defined as the ratio of the maximum of detail components to the local mean of the corresponding approximate component. The visual experiments and quantitative assessments demonstrate the effectiveness of this method compared to present image fusion schemes, especially for medical diagnosis. Keywords: wavelet coefficient Contrast, medical image fusion, edge preservation, performance evaluation, Medical diagnosis. Introduction In recent years, multimodality medical image fusion has drawn lots of attention with the increasing rate at which multimodality medical images are available in many clinic application fields. Radiotherapy plan, for instance, often benefits from the complementary information in images of different modalities. Dose calculation is based on the computed tomography (CT) data, while tumor outline is often better performed in the corresponding magnetic resonance (MR) image. For medical diagnosis, CT provides the better information on denser tissue with less distortion,while MRI offers better information on soft tissue with more distortion.With more available multimodality medical images in clinic application, the idea of encompassing different image information comes up very important ,and medical image fusion has been emerging as a new and promising research area. The goal of image fusion is to obtain useful Complementary information from multimodality images as much as possible. The simplest way to obtain a fused image from two or more medical images is to average them. Although mostly preserving the original meaning of the images, it is prone to reduce the contrast of the fused image. With developments of Marr’s vision and applications of multi-resolution image processing techniques, the potential benefits of multi-scale,multi- resolution image fusion schemes like Laplacian pyramid based and gradient pyramid based image fusion methods have been explored in order to improve the contrast of the fused image.A wavelet pyramid method is a scheme which can exact the localized characteristics of input images. Multi-scale pyramid, which is over-complete representation of the original images, to merge different images into a single one to adapt the invariance with respect to elementary geometric operations such as translation, scaling, and rotations. Most of present image fusion methods aim at obtaining as many as information from the different modality images. The fusion criterion is to minimize different error between the fused image and the input images. With respect to the medical diagnosis, the edges and outlines of the interested objects is more important than other information. Therefore, how to preserve the edge-like features is worthy of investigating for medical image fusion. As we know, the image with higher contrast contain more edge-like features. In term of this view, we proposed a new medical image fusion scheme based on an improved wavelet coefficient contrast. In section 2, the wavelet transform is discussed and then we define a new wavelet coefficient contrast . The image fusion Scheme is described in detail in the section 3.Finally , different image fusion scheme on the medical