Tukey's Biweight constrain function for a surrogate image enlargement based on SISR algorithm using high spectrum estimation

Abstract

Consistently, the classical image enlargement algorithm is a scientific analytical method for producing a better refined resolution image that is frequently required for advanced digital image processing (DIP) from a single lower resolution image that is frequently acquired from digital camera embedded system. Because of its less computation calculation, the Single-Image Super-Resolution (SISR) that analytically applied for a single lower resolution image is one of the worldwide effective Super Resolution-Reconstruction (SRR) algorithms thus this paper proposes the image enlargement based on the SISR algorithm using high spectrum estimation and Tukey's Biweight constrain function. In general, the performance of this SISR algorithm is hinge on up to three parameters (b, h, k) however there are burdensome for determining these optimized values for these parameters (b, h, k). In order to solve this problem, the Tukey's Biweight constrain function, which is hinge on merely single parameter (T), contrary to three parameters like the classical constrain function, is engaged in the SISR algorithm. By examining on 14 benchmark images, which are profaned by considerable noise forms, in scientific analytical scrutinizing sector, the novel SISR algorithm illustrates that there is efficiently and effortlessly in parameter setting process but the performance of the novel SISR algorithm (with single parameters) is nearly equal to the original SISR (with three parameters). Due to greatly time reduction in the parameter setting process, this novel SISR algorithm is more advisable for real-time applications.