Cuckoo search constrained gamma masking for MRI image contrast enhancement

Poor quality images in Magnetic Resonance Imaging (MRI) may not provide enough information for visual interpretation of the affected areas of the human body. Cuckoo Search Constrained Gamma Masking for MRI Image Contrast Enhancement is a novel adaptive image enhancement technique described in this paper to improve image views and give computational support. Nature-inspired algorithms are widely applied in the arena of image enhancement for various optimization purposes. Cuckoo search is one of the prominent nature-inspired performance algorithms that we employed in this work for the enhancement of magnetic resonance imaging (MRI). We proposed a wavelet-based masking technique employing a cuckoo search algorithm whose masking value is corrected by gamma function for the contrast enhancement of MRI images. The cuckoo search algorithm can inevitably fine-tune the relation of nest building using genetic operatives like adaptive cusp and alteration. The proposed contrast enhancement scheme is examined quantitatively for different types of MRI images. Extensive simulation results compared with quantitative values have revealed that the traditional nest building of cuckoo search optimization is improved by adaptive gamma correction. Comparative analysis with the existing works establishes the usefulness of the proposed methodology over the other standard approaches.