Digital Image Processing

K. P. Indira ¹, R. Rani Hemamalini ²

Affiliations
1 Sathyabama University, Chennai, IN
2 St.Peter’s College of Engineering, Chennai, IN

Abstract

The aim of medical image fusion is defined as the combination of visual information contained in any number of input images into a single fused output image without introducing artifacts or information loss. In this paper medical image fusion based on discrete wavelet transform (DWT) has been proposed for positron emission tomography and computed tomography images. Initially the input images are decomposed into low and high frequency coefficients by DWT. Fusion of images are obtained by applying choose max fusion rule for low frequency coefficients and choose max and contrast fusion rule for high frequency coefficients. Finally to reconstruct the original image inverse transform is applied. Qualitative and quantitative fusion results show that contrast method performs well than choose max method.

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K. P. Indira ¹, R. Rani Hemamalini ²

Affiliations
1 Sathyabama University, Chennai-119, IN
2 St. Peter's College of Engineering and Technology, Chennai, IN

Abstract

There are some existing methods to enhance contrast restoration but do not provide considerable visibility enhancement. In this paper the contrast of the image is corrected and then enhanced. Initially estimating a measure of degradation and its removal is given and at last wavelet fusion method is used to enhance the image. Medical image processing has been investigated for more than three decades. It is clear that medical imaging will still play a very dominant role in clinical research as well as in the daily routine practice in the coming decade. For a number of reasons the images obtained by the medical instruments itself, such as CT, MRI, PET, SPECT etc. are insufficient for the efficient performance of a surgical intervention and various image processing techniques are necessary in order to make the most important features more easily visible to diagnose. In addition, contrast correction allows a doctor to observe functional abnormalities that are not visible on a regular scan. Owing to its rapidly increasing popularity over the last few decades, the wavelet transform has become a quite standard tool in numerous image research and its application domains.

Keywords

Adding Contrast, Brightness Normalization, Image Enhancement.

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