Contrast Enhancement for MRI Image Using Hybrid Optimization Technique

Abstract

            The contrast enhancement in MRI image is a wide application in many real world applications like medical application areas and photographic images. The main key problem medical image processing is the poor contrast level enhancement. The nature of poor contrast enhancement is improved using the contrast nature of MR image is improved using a Binary Flower Pollination Algorithm and Binary Particle Swarm Optimization (BFPA-BPSO). The level of contrast nature in Magnetic Resonance Image (MRI) is improved to eliminate the degradation in images at the time of image acquisition process. By improving the contrast of the medical MRI image by taking the four different images as lung, breast, brain and thyroid MRI images. And also in this study presents to recognize spatial information for image enhancement. The cost function is integrated with contrast measure based on few metrics to create a newer transformation function. The timing complexity can be reduced using soft-computing approaches and it increases the search pattern using a transformation function in spatial domain. This method improves the pixel intensity to increase the resolution of an image. The performance evaluation of this method is estimated by using three different parameter as PSNR, SSIM and accuracy.