Edge Preserving Image Fusion Using RMS Contrast and Linear Prediction Model
This work focuses on enhancing the visual quality of medical images obtained using X-Ray, MRI and CT modalities through edge preserving image fusion techniques. This would be helpful for doctors in analysis and treatment planning, as it provides a better visualization of the images under consideration. The fusion of the images has done using Root Mean Square (RMS) based perceptual contrast measure and a linear prediction (LP) based edge extraction method. To assess the performance of the proposed fusion scheme, the results obtained are analyzed using the following quality metrics say, Universal Image Quality Index, Structural Similarity Index Measure (SSIM), Fusion Mutual Information (FMI), Structural Content and Entropy Measure, which are suitable when the ground truth is not available for comparison.
