Design of spatial filter for fused CT and MRI brain images

Noise is an ingrained phenomenon in the medical images which may increase the root mean square error and reduce the peak signal to noise ratio. Regardless of the actuality that the noise itself carries some information about the illuminated area, the appearance of image gets deteriorated. Hence there is a need for reducing the noise and this paper explains about the denoising method using non local means filter and shrinkage rule. NLM filter is used for the removal of speckle noise and shrinkage rule is used to shrink the content of noise present in the brain images by means of the thresholding technique. In the thresholding method, the shrinkage coefficient is compared with the threshold value and if it is smaller, it gets eliminated to reduce the noise while preserving the edges. The proposed filtering technique is used along with the Curvelet transform and Wavelet transform and it is observed that the Curvelet transform produces better result when compared with the Wavelet transform. The simulation results have proved that this method actively removes the noise and reduces the root mean square error while increasing the image enhancement factor and peak signal to noise ratio.