Linear Methods for Image Interpolation Pascal Getreuer CMLA, ENS Cachan, France ([email protected])
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A Comparative Analysis of Image Interpolation Algorithms
ISSN (Online) 2278-1021 IJARCCE ISSN (Print) 2319 5940 International Journal of Advanced Research in Computer and Communication Engineering Vol. 5, Issue 1, January 2016 A Comparative Analysis of Image Interpolation Algorithms Mr. Pankaj S. Parsania1, Dr. Paresh V. Virparia2 Research Scholar, Department of Computer Science, Sardar Patel University, Vallabh Vidyanagar, Gujarat, India1 Director, Department of Computer Science, Sardar Patel University, Vallabh Vidyanagar, Gujarat, India2 Abstract: Image interpolation is the most basic requirement for many image processing task such as computer graphics, gaming, medical image processing, virtualization, camera surveillance and quality control. Image interpolation is a technique used in resizing images. To resize an image, every pixel in the new image must be mapped back to a location in the old image in order to calculate a value of new pixel. There are many algorithms available for determining new value of the pixel, most of which involve some form of interpolation among the nearest pixels in the old image. In this paper, we used Nearest-neighbor, Bilinear, Bicubic, Bicubic B-spline, Catmull-Rom, Mitchell- Netravali and Lanzcos of order three algorithms for image interpolation. Each algorithms generates varies artifact such as aliasing, blurring and moiré. This paper presents, quality and computational time consideration of images while using these interpolation algorithms. Keywords: Nearest-neighbor, Bilinear, Bicubic, Bicubic B-spline, Catmull-Rom, Mitchell-Netravali, Lanzcos. I. INTRODUCTION Image interpolation is a term used for image processing, Interpolation using Shape-Preserving Approach [4], but is often used with different terminologies in literature classification and stitching [5], grid based image like image scaling, image resampling and image resize. -
University of California, San Diego
UNIVERSITY OF CALIFORNIA, SAN DIEGO Pattern Recognition Techniques for Image and Video Post-Processing: Speci¯c Application to Image Interpolation A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Electrical and Computer Engineering by Karl S. Ni Committee in charge: Professor Truong Q. Nguyen, Chair Professor Yoav Freund Professor Gert Lanckriet Professor William Hodgkiss Professor Nuno Vasconcelos 2008 Copyright Karl S. Ni, 2008 All rights reserved. The dissertation of Karl S. Ni is approved, and it is acceptable in quality and form for publication on micro¯lm: Chair University of California, San Diego 2008 iii To My Family. I owe you everything. The true path of success is paved by diligence inspired by passion. |Unknown iv TABLE OF CONTENTS Signature Page . iii Table of Contents . v List of Figures . viii List of Tables . x Acknowledgements . xi Vita and Publications . xiv Abstract . xvi 1 Introduction . 1 1.1 Towards a Shift in Computational Focus . 3 1.2 Image Interpolation . 7 1.3 Focus of This Work . 7 2 Background . 9 2.1 Non-statistical Superresolution Methods . 10 2.2 Learning-Based Superresolution Methods . 11 3 Image Patch-Based Distribution . 15 3.1 A Distribution Model for Image Patches . 17 3.2 Empirical Justi¯cation . 18 3.3 Using the Proposed Model . 22 3.4 Implications in Di®erent Domains . 23 3.5 On the Variability of Finite Data Sets . 27 3.6 Results . 27 3.7 Summary . 30 3.8 Acknowledgements . 30 4 Adaptive k-Nearest Neighbor for Image Interpolation . 31 4.1 Review of k-Nearest Neighbor for Regression . -
Extensible Implementation of Reliable Pixel Art Interpolation
F O U N D A T I O N S O F C O M P U T I N G A N D D E C I S I O N S C I E N C E S Vol. 44 (2019) No. 2 ISSN 0867-6356 DOI: 10.2478/fcds-2019-0011 e-ISSN 2300-3405 Extensible Implementation of Reliable Pixel Art Interpolation Paweł M. Stasik, Julian Balcerek ∗ y Abstract. Pixel art is aesthetics that emulates the graphical style of old computer systems. Graphics created with this style needs to be scaled up for presentation on modern displays. The authors proposed two new modifications of image scaling for this purpose: a proximity-based coefficient correction and a transition area restriction. Moreover a new interpolation kernel has been introduced. The presented approaches are aimed at reliable and flexible bitmap scaling while overcoming limitations of exist- ing methods. The new techniques were introduced in an extensible .NET application that serves as both an executable program and a library. The project is designed for prototyping and testing interpolation operations and can be easily expanded with new functionality by adding it to the code or by using the provided interface. Keywords: image processing, pixel art, image upscaling, bitmap interpolation, proximity measure, proximity-based coefficient correction (PBCC), p-lin interpola- tion, transition area restriction (TAR) 1. Introduction Old computer systems, in comparison to modern systems, were heavily restricted in their graphical capabilities (in the sense of the amount of available colors and the possible resolutions). Pixel art is an artistic form that was aimed at handling these limitations, but them should not prevent it from being presented with graphical possibilities of the modern systems. -
3D LANCZOS INTERPOLATION for MEDICAL VOLUMES Thiago
15th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering and 3rd Conference on Imaging and Visualization CMBBE 2018 P. R. Fernandes and J. M. Tavares (Editors) 3D LANCZOS INTERPOLATION FOR MEDICAL VOLUMES Thiago Moraes1, Paulo Amorim1, Jorge Silva1 and Helio Pedrini2 1Division of 3D Technologies, Center for Information Technology Renato Archer Campinas-SP, Brazil, 13069-901 2Institute of Computing, University of Campinas Campinas, SP, Brazil, 13083-852 Keywords: Image Interpolation, Resampling, Medical Imaging. Abstract: Medical imaging techniques have been widely used in the diagnosis and treatment of many diseases, such as magnetic resonance imaging, computed tomography, mammography, ultrasonography, and photon emission tomography. Their main purpose is to enable the visu- alization of internal anatomic structures, such as organs and tissues, for clinical procedures. Resampling is required for certain medical tasks, for instance, registration and reconstruction, which occur when images or volumes are scaled, translated or rotated. The result of the re- sampling depends on the interpolation filter. In this paper, we develop and analyze a novel three-dimensional Lanczos resampling method in the context of medical imaging. 1. INTRODUCTION In the context of numerical analysis, interpolation techniques [12–15, 19, 21–23] aim to con- struct new data points from a set of known samples. In the field of image analysis, resampling techniques [9, 21, 23] transform a sampled image from one coordinate system to another. Resampling is typically employed to create a new version of an image with a different dimension. The increase and reduction of an image are called upsampling and downsampling, respectively. Image interpolation and resampling techniques play an important role in several biomed- ical applications, such as data reslicing, image registration, tomographic reconstruction, and volumetric rendering [23]. -
Image Zooming Using Wavelet Coefficients
IMAGE ZOOMING USING WAVELET COEFFICIENTS Dissertation submitted in partial fulfillment of the requirements for the award of degree of Master of Technology in Computer Science and Applications Submitted By Himanshu Jindal (Roll No. 651103003) Supervised By Dr. Singara Singh Assistant Professor SCHOOL OF MATHEMATICS AND COMPUTER APPLICATION THAPAR UNIVERSITY PATIALA – 147004 July 2014 CERTIFICATE I hereby certify that the work being presented in the dissertation entitled, "Image Zooming Using Wavelet Coefficients", in partial fulfillment of the requirements for the award of degree of Master of Technology in Computer Science and Applications submitted to the School of Mathematics and Computer Applications of Thapar University, Patiala, is a authentic record of my own work carried out under the supervision of Dr. Singara Singh and refers other researcher's work which are duly listed in the reference section. The matter presented in the dissertation has not been submitted for the award of any other desree of this or anv other university. _ .. \,. ->- PL*"*?irf t (Himanshu Jindal) This is to certify that the above statement made by the student is correct and true to the best of my knowledge. ffi1,, (Dr. Singara Singh) Assistant Professor, School of Mathematics and Computer Applications, Thapar University, Patiala Countersigned By - n r / /t I T" \^--Y H4W-- Dr. Rajesh Kumar Dr. S.K. Nlohdpatfa Head, Dean School of Mathematics and Computer Applications, (AcademicAffairs) Thapar University, Patiala Thapar University, Patiala ACKNOWLEDGMENT I would like to acknowledge everyone who supported me during my experience at Thapar University and my work on this dissertation. First and foremost I would like to thank God for providing me with faith, self-confidence and ability to complete the dissertation.