Interpolation is a common technique for predicting unknown data points within the range of discrete known data points. In image processing and analysis applications, image interpolation is employed for changing image resolution but also for tasks like image rotation and other transformations. Classical image interpolation algorithms such as nearest neighbour, bilinear and bicubic interpolation ...

Image resampling method using color edge-directed interpolation has been developed. It uses color image gradient to perform the interpolation across image gradient rather than along image gradient. The developed combined method takes color low resolution image and grayscale high resolution image obtained by a non-linear image resampling method as an input. It includes consecutive calculation st...

We discuss possible algorithms for interpolating data given in a set of curves and/or points in the plane. We propose a set of basic assumptions to be satis ed by the interpolation algorithms which lead to a set of models in terms of possibly degenerate elliptic partial di erential equations. The Absolute Minimal Lipschitz Extension model (AMLE) is singled out and studied in more detail. We sho...

This paper presents some new techniques for high resolution (HR) image processing and compares between them. The paper focuses on two main topics, image interpolation and image superresolution. By image interpolation, we mean extracting an HR image from a single Degraded low resolution (LR) image. Polynomial based image interpolation is reviewed. Some new techniques for adaptive image interpola...

Image enhancement is an important processing task in image processing field. By applying image enhancement, blur or any type of noise in the image can be removed so that the resultant image quality is better. Image enhancement is used in various fields like medical diagnosis, remote sensing, agriculture, geology, oceanography. There are numbers of techniques for image enhancement. Image interpo...

Image magnification algorithms directly affect the quality of image magnification. In this paper, based on the image interpolation algorithm principle, features of the nearest neighbor interpolation, bilinear interpolation, bicubic interpolation and cubic B spline interpolation were analyzed. At the same time, their advantages and disadvantages were compared. In the experiment, image magnificat...

We consider the problem of image interpolation from an adaptive optimal recovery point of view. Many different standard interpolation approaches may be viewed through the prism of optimal recovery. In this paper we review some standard image interpolation methods and how they relate to optimal recovery as well as introduce a broader, more general and systematic approach to image interpolation u...

Abstract— Image interpolation is widely used in many image processing applications, such as digital camera, mobile phone, tablet and display devices. Image interpolation is a method of estimating the new data points within the range of discrete set of known data points. Image interpolation can also be referred as image scaling, image resizing, image re-sampling and image zooming. This paper pre...

The interpolation task plays a key role in the reconstruction of high-resolution image quality in superresolution algorithms. In fact, the foremost shortcoming encountered in the classical interpolation algorithms, is that they often work poorly when used to eliminate blur and noise in the input image. In this sense, the aim of this work is to develop an interpolation scheme for the purpose of ...