This work presents a discussion about multi-frame Super-Resolution Reconstruction (SRR) and single-frame interpolation. SRR has been extensively studied in the last decades but it is not yet as popular as image interpolation. Since both methods are directed to improve image quality, comparisons are inevitable and desirable. However, fundamental misunderstandings can still be found in the litera...

In Image upscaling, a higher resolution image is processed from an available low resolution image. There are numerous scenarios and applications where image upscaling is required and performed. The paper proposes a simple image scaling algorithm and implements it with a fuzzy variant of the supervised ART neural network, ARTMAP. The method has been compared with nearest neighbor interpolation, ...

The problem of digital signal and image resampling with discrete sinc interpolation is addressed. Discrete sine interpolation is theoretically the best one among the digital convolution-based signal resampling methods because it does not distort the signal as defined by its samples and is completely reversible. However, sinc interpolation is frequently not considered in applications because it ...

A resolution enhancement scheme is presented. It consists of interpolation followed by processing with an adaptive nonlinear forward-and-backwarddi usion process that enhances edges while suppressing interpolation ringings and denoising smooth areas. keywords: super-resolution, image interpolation, anisotropic di usion, image enhancement, scale-space.

This paper proposes a fast and effective image interpolation algorithm using median filter. The interpolation algorithm is composed of two steps. First, a non-linear iterative procedure is utilized to interpolate the pixel whose direction can be easily determined by local information. Second, according to the introduced assumption that image interpolation can be regarded as a local image filter...

Method for image prediction with nonlinear control lines which are derived from extracted feature points from the previously acquired imagery data based on Kriging method and morphing method is proposed. Through comparisons between the proposed method and the conventional linear interpolation and widely used Cubic Spline interpolation methods, it is found that the proposed method is superior to...

A dual tree complex wavelet transform (DT -CWT)based directional interpolation scheme for denoising of noisy images is proposed . The problems of denoising and interpolation are modeled as to estimate the noiseless and missing samples under the same framework of optimal estimation. Initially, DT -CWT is used to decompose an input low-resolution noisy wage irito low and high frequency subbands. ...

This chapter presents a survey of interpolation and resampling techniques in the context of exact, separable interpolation of regularly sampled data. In this context, the traditional view of interpolation is to represent an arbitrary continuous function as a discrete sum of weighted and shifted synthesis functions—in other words, a mixed convolution equation. An important issue is the choice of...

Assumptions about image continuity lead to oversmoothed edges in common image interpolation algorithms. A wavelet-based interpolation method that imposes no continuity constraints is introduced. The algorithm estimates the regularity of edges by measuring the decay of wavelet transform coefficients across scales and preserves the underlying regularity by extrapolating a new subband to be used i...

Evaluation and analysis of most remotely sensed data requires careful image-to-image registration or ortho-rectification (geocoding). Photogrammetric practice has shown that polynomial transformation functions are useful for registration of aerial photographs. However, multiand hyperspectral remotely sensed data are often recorded by airborne line scanners. Then ortho-rectification by conventio...