An Extra-Rate Spatial Enhancement Constructed by MSRR using Regularized Technique and SSRR using High-Frequency Pre-Forecasting

Abstract

Under many circumstances, a high spatial resolution image (HR) is greatly needed for modern applications nevertheless the HR image captured device is usually overpriced cost. Hence, Super Resolution Reconstruction (SRR) technique, which can reconstruct a HR image from a single LR image or many LR images by using algebraic formulation, is one of the modern research fields in digital image processing (DIP) and Computer Vision (CV). In this paper, an extra-rate spatial enhancement constructed by MSRR (Multi-frame Super Resolution Reconstruction) using regularized technique and SSRR (Single-frame Super Resolution Reconstruction) using high-frequency pre-forecasting is presented in order to enlarge up to 16x ratio rate. Initially, a group of captured images with low spatial resolution are mathematically fused by MSRR using regularized technique established on a recursive Maximum Likelihood and Tukey's Biweight norm in order to enlarge up to 4x ratio rate. Next, this 4x enhanced image is enlarged to be 16x spatial resolution image by SSRR established on the high-frequency pre-forecasting. In the verification experimentation section, the verification outcome demonstrates that the proposed spatial enhancement is successful for enlarging HR image with 16x ratio rate with finer quality.