<p>Advances in local image statistical analysis have made possible the random-valued impulse noise detection but the current noise detections based on ROAD (Rank-Ordered Absolute Differences), ROLD (Rank-Ordered Logarithmic Differences) and RORD (Rank-Ordered Relative Differences), which are the most three effective and practical detections using the local image statistical characteristic, operates effectively on different noise density and different image statistical characteristic. To address these issues, this paper proposes the comparative analysis on the noise detections based on ROAD, ROLD and RORD. Therefore, the first contribution is the comparative statistical distribution of these three noise detections. By comprehensive experiment at each noise density, the optimized detected threshold is later determined from four benchmark data: Lena, Girl, Pepper and Airplane. Moreover, the maximum detection accuracy for each case is comparatively demonstrated by using the noise detections based on ROAD, ROLD and RORD with the optimized detected threshold.</p>
Because of the feasible and impressive fallout, the classical Super-Resolution Reconstruction (SRR) is the contemporary algorithm for improving spatial information and reducing noise and SISR (Single-Image Super-Resolution) method, which is form on the classical SRR, is solely developed for improving spatial information. Disastrously, deficiency of the classical SISR method is conceptually computed from three specifications (b, h, k) and the simulating calculation of the optimized specifications for interpolating the better and higher spatial information images with highest PSNR is so burdersome. For figuring out this issue, the Geman&McClure function is proposed to replace with the ordinary SISR function because this function is conceptually computed from only one specification (T), contrary to three specifications similar to classical SISR method hence this analytic article focuses to offer a novel elementary spatial expanding scheme form on SISR method with modifying Geman&McClure function. Therefore, the fallout of a proposed spatial expanding scheme approximately matches to classical SISR method. From these reason, a novel elementary spatial expanding scheme is easily implemented for real works.
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