In this paper, a new method for gray-scale image and color zooming algorithm based on their local information is offered. In the proposed method, the unknown values of the new pixels on the image are computed by Moving Least Square (MLS) approximation based on both the quadratic spline and Gaussian-type weight functions. The numerical results showed that this method is more preferable to biline...

Background: High-resolution medical images often need to be downsampled because of the memory limitations hardware used for machine learning. Although various image interpolation methods are applicable downsampling, effect data preprocessing on learning performance convolutional neural networks (CNNs) has not been fully investigated. Methods: In this study, five different pixel algorithms (near...

In this article, we address the problem of interpolating data points lying on a regular grid by C 1-continuous L1-bicubic spline surfaces. Our algorithm is based on a local univariate L1 minimization method which enable us to calculate first derivative values for C 1-cubic spline curves. In order to construct the interpolation surface, we calculate four derivative values at each data point usin...

Image interpolation is one of key contents in image processing. We present an interpolation algorithm based on a rational function model with constraint parameters. Firstly, based on the construction principle of the rational function, the detection threshold is selected through contour analysis. The smooth and non-smooth areas are interpolated by bicubic interpolation and general rational inte...

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...

BACKGROUND Unstable carotid plaques on subjective, visual, assessment using B-mode ultrasound scanning appear as echolucent and heterogeneous. Although previous studies on computer assisted plaque characterisation have standardised B-mode images for brightness, improving the objective assessment of echolucency, little progress has been made towards standardisation of texture analysis methods, w...

This paper presents the nearest neighbor value (NNV) algorithm for high resolution (H.R.) image interpolation. The difference between the proposed algorithm and conventional nearest neighbor algorithm is that the concept applied, to estimate the missing pixel value, is guided by the nearest value rather than the distance. In other words, the proposed concept selects one pixel, among four direct...

The interpolation algorithm plays an essential role in the digital image correlation (DIC) technique for shape, deformation, and motion measurements with subpixel accuracies. At the present, little effort has been made to improve the interpolation methods used in DIC. In this Letter, a family of recursive interpolation schemes based on B-spline representation and its inverse gradient weighting ...

In this paper, we propose a novel self-learning based single-image super-resolution (SR) method, which is coupled with dual-tree complex wavelet transform (DTCWT) based denoising to better recover high-resolution (HR) medical images. Unlike previous methods, this self-learning based SR approach enables us to reconstruct HR medical images from a single low-resolution (LR) image without extra tra...