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Image Interpolator

by Livio Tenze And, Livio Tenze, Sergio Carrato
"... In this paper we present an innovativeinterpolator which performs high quality N \Theta interpolation on both synthetic and real world images. Its structure, which is based on a rational operator, provides edge sensitive data interpolation, so that sharp and artifact free images are obtained. 1 INT ..."
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In this paper we present an innovativeinterpolator which performs high quality N \Theta interpolation on both synthetic and real world images. Its structure, which is based on a rational operator, provides edge sensitive data interpolation, so that sharp and artifact free images are obtained. 1

Image Interpolation

by Vicent Caselles, Simon Masnou, Jean-Michel Morel, Catalina Sbert - PROCEEDINGS OF THE SIX INTERNATIONAL WORLD WIDE WEB CONFERENCE , 1998
"... 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 satisfied by the interpolation algorithms which lead to a set of models in terms of possibly degenerate elliptic partial differential equations. T ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
. The Absolute Minimal Lipschitz Extension model (AMLE) is singled out and studied in more detail. We show experiments suggesting a possible application, the restoration of images with poor dynamic range. We also analyse the problem of unsmooth interpolation and show how it permits a subsidiary variational

Regularity-Preserving Image Interpolation

by W. Knox Carey, Daniel B. Chuang, Sheila S. Hemami - IEEE Transactions on Image Processing , 1997
"... Common image interpolation methods assume that the underlying signal is continuous and may require that it possess one or more continuous derivatives. These assumptions are not generally true of natural images, most of which have instantaneous luminance transitions at the boundaries between objects. ..."
Abstract - Cited by 59 (1 self) - Add to MetaCart
Common image interpolation methods assume that the underlying signal is continuous and may require that it possess one or more continuous derivatives. These assumptions are not generally true of natural images, most of which have instantaneous luminance transitions at the boundaries between objects

An Axiomatic Approach to Image Interpolation

by Vicent Caselles, Jean-Michel Morel, Catalina Sbert , 1998
"... 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 satisfied by the interpolation algorithms which lead to a set of models in terms of possibly degenerate elliptic partial differential equations. The ..."
Abstract - Cited by 126 (8 self) - Add to MetaCart
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 satisfied by the interpolation algorithms which lead to a set of models in terms of possibly degenerate elliptic partial differential equations

Image Interpolation Techniques Review

by Reetumala Thakre, Prof Rajendra Singh
"... Abstract- image interpolation is very interesting areaof research in image processing which consists of various processing tasks such as compression, restoration, denoising, enhancement. Reconstruction quality of any image interpolation algorithm depends on it’s ability to adapt changing pixel struc ..."
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Abstract- image interpolation is very interesting areaof research in image processing which consists of various processing tasks such as compression, restoration, denoising, enhancement. Reconstruction quality of any image interpolation algorithm depends on it’s ability to adapt changing pixel

Edge Inference for Image Interpolation

by Neil Toronto
"... Abstract — Image interpolation algorithms try to fit a function to a matrix of samples in a “natural-looking ” way. This paper presents edge inference, an algorthm that does this by mixing neural network regression with standard image interpolation techniques. Results on gray level images are presen ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
Abstract — Image interpolation algorithms try to fit a function to a matrix of samples in a “natural-looking ” way. This paper presents edge inference, an algorthm that does this by mixing neural network regression with standard image interpolation techniques. Results on gray level images

Image Interpolation and Resampling

by Thierry Blu, Michael Unser - Handbook of Medical Imaging, Processing and Analysis , 2000
"... Abstract—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 shi ..."
Abstract - Cited by 80 (11 self) - Add to MetaCart
Abstract—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

View Interpolation for Image Synthesis

by Shenchang Eric Chen, et al.
"... Image-space simplifications have been used to accelerate the calculation of computer graphic images since the dawn of visual simulation. Texture mapping has been used to provide a means by which images may themselves be used as display primitives. The work reported by this paper endeavors to carry t ..."
Abstract - Cited by 605 (0 self) - Add to MetaCart
this concept to its logical extreme by using interpolated images to portray three-dimensional scenes. The special-effects technique of morphing, which combines interpolation of texture maps and their shape, is applied to computing arbitrary intermediate frames from an array of prestored images. If the images

Mathematical Techniques for Image Interpolation

by Todd Wittman , 2005
"... We discuss the problem of interpolating visually acceptable images at a higher resolution. We first present the interpolation problem and why linear interpolation filters are inadequate for image data. To represent the major mathematical approaches to image processing, we discuss and evaluate five d ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
We discuss the problem of interpolating visually acceptable images at a higher resolution. We first present the interpolation problem and why linear interpolation filters are inadequate for image data. To represent the major mathematical approaches to image processing, we discuss and evaluate five

PDE-BASED IMAGE INTERPOLATORS

by Youngjoon Cha, Seongjai Kim
"... We present a PDE-based interpolation algorithm to effectively reproduce high resolution im-agery. Conventional PDE-based interpolation methods can produce sharp edges without checker-board effects; however, they are approximators and tend to weaken fine structures. In order to overcome the drawback, ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
, a texture enhancement method is incorporated as a post-process of PDE-based interpolation methods. The post-process turns out to make the resulting algorithm an interpolator. It has been numerically verified that the resulting algorithm, called the PDE-based image interpolator (PII), restores sharp
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