Super-resolution image reconstruction using interpolation-based method for biometric images

Super-resolution is a widely applied technique in enhancing image resolution. It has uses in medical imaging, satellite imaging and especially in biometric identifications. Three main methods in super-resolution are learning-based, reconstruction-based, and interpolation-based methods. The learning-based methods often requires big, external data and the resultant image output relies heavily on the features of the training image data while reconstruction-based methods were based on the presumption of the low-resolution image is a degraded version of a high-resolution image and the computational complexity that were required to reverse the degradation were often high and the resulting output image quality were inconsistent. This research proposed a Gabor-weighted interpolation method to super resolve a low-resolution image into a high-resolution image since the common problem in an interpolation-based method was its tendency to create edge artifacts, jaggedness or over-smoothing. The Gabor-weighted interpolation was done only at the edge areas of an image and utilised the Lanczos interpolation to interpolate the non-edge areas. The proposed method was analysed quantitatively and qualitatively and also included multiple edge-based analysis. The proposed method was compared to other super-resolution methods including learning-based, reconstruction-based, interpolation-based, and hybrid methods. The results showed that the proposed method provide a good Image Quality Assessment (IQA) results consistently across the tested images and the application of the proposed method on biometric images provide good results with a high Fingerprint Matching score compared to other methods which is 1703.475. The proposed method yielded an average of 33.698 Peak Signal-to-Noise Ratio (PSNR) value and 16.177 Edge-Based Image Quality Assessment (EBIQA) value for the general images and an average of 35.621 PSNR value and 18.608 EBIQA value for biometric images. The proposed method also yielded clear and pleasing effects on the high-resolution images based on the naked eye comparison presented.