Medical Image Fusion using Rayleigh Contrast Limited Adaptive Histogram Equalization and Ant Colony Edge Method

Image fusion can be broadly defined as the process of combing multiple input images into a single image without the introduction of distortion or loss of information. The motive of fusion of images is representing the relevant information from many individual images in a single image. Fusion is an important technique and is widely used in many fields such as remote sensing, robotics and medical applications. The term image fusion becomes important in the field of medical for the fusion of medical images known as medical image fusion. Medical image fusion is used to fulfill clinic requirements such as for the purpose of diagnosis and treatment. As there are various imaging modalities used in medical image fusion like MRI, CT, PET, SPECT etc. Hence to get complete, detailed and accurate information these images are to be fused. The propose work is Image Fusion using Rayleigh CLAHE (Contrast Limited Adaptive Histogram Equalization) and Ant colony Edge method. In the proposed method there is a fusion of MRI and CT images then histogram plot of both images are equalized by using the Contrast Limited Adaptive Histogram Equalization. Finally the edges of fused image that contains information are prevented from distortion by using Ant Colony Edge Method. The result parameters of propose technique is compared with Histogram equalization of MRI and CT images using Canny Edge Detection Method. The purpose of this is also to provide a comprehensive review of the existing literature available on image fusion and its quality metrics from already proposed techniques. The results are obtained by using MATLAB language and tools.