Image interpolation ppt. of CSEE West Virginia University.

Image interpolation ppt This is PowerPoint's way of trying to blur pixelation as you scale a small image to a larger size. Good compromise between processing time and output quality Standard in many image editing programs, printer Most image viewing and editing software use this type of interpolation to enlarge a digital image for the purpose of closer examination because it does not change the color information of the image and does not introduce any anti-aliasic. I get into the habit of looking for large images and graphics only. In the context of data analysis and visualization, interpolation plays a crucial role in enhancing the accuracy and clarity of presentations created using PowerPoint (PPT). Combination of view synthesis and morphing - Chen and Williams, 1993 - Seitz and Dyer Video view interpolation Fewer cameras Smooth Motion Automatic and Real-time rendering Prior work: IBR (static) The Lumigraph Gortler et al. , SIGGRAPH ‘96 Concentric Mosaics Shum & He, SIGGRAPH ‘99 Plenoptic Modeling McMillan & Bishop, SIGGRAPH ‘95 Light Field Rendering Levoy & Hanrahan, SIGGRAPH ‘96 Prior work: IBR (dynamic) Free Zooming is one of the important concepts of image processing. Jan 6, 2022 · This is a 22-lecture series on Image Processing that I have created over the past 23 years (1999-2021) for my course, EECE 4353 / 5353, at the Vanderbilt University School of Engineering. Casta ñeyra Juan Valera Domingo Rodriguez University of Puerto Rico at Mayaguez 9/23/2009. Dec 29, 2018 · In the previous blog, we discussed image interpolation, its types and why we need interpolation. Interpolation produces a function that matches the given data exactly. View Tutorials image interpolation PowerPoint (PPT) presentations online in SlideServe. If you want a large pixelated looking image, you will need to find a large or high resolution version of that image for you to insert into PowerPoint. Ee465: digital zooming and image inpainting are examples of digital image processing. CCD arrays are commonly used in digital cameras to capture images as arrays of pixels. Image interpolation refers to the "guess" of intensity values at missing locations. The method uses Lagrange polynomials to find an nth degree polynomial approximation to a function based on a set of points. IMAGE RECONSTRUCTION ALGORITHM. In most cases it is not realistic to ask for the value \ (f (x, y)\): a unique value only exists in case the sampling proces is without loss of information. The document discusses color image processing, categorizing it into full-color and pseudo color processing. Interpolation Problem f *: known image values • f : unknown values over region Ω • Assuming scalar image values Jan 8, 2025 · Learn about intensity transformations and spatial filtering methods for manipulating image pixels. some algorithms for image interpolation - Download as a PDF or view online for free Feb 12, 2024 · Learn about different methods of intelligent interpolation for image enlargement, including constant interpolation, linear interpolation, bilinear interpolation, bicubic interpolation, and more. It describes Newton's divided difference interpolation polynomials which use higher order polynomials to fit additional data points. - View online for free Jul 31, 2025 · Interpolation is a technique in Statistics to determine an approximation of a mathematical statement by using any intermediate value for the independent variable. There are three main types of image sensors: single, line, and array. If you insert the same picture at HD1080p size but with the DPI set to 144, it’ll get inserted at 100% scale and fit the slide exactly. pdf) format and MS Powerpoint (. It works by using known pixel data to estimate values at unknown points. 4. Given (x 0 ,y 0 ), (x 1 ,y 1 ), …, (x n ,y n ), finding the value of ‘y’ at a value of ‘x’ in ( x 0, x n ) is called interpolation. It describes two main techniques for zooming images: nearest neighbor interpolation and bilinear interpolation. INTERPOLATION. Interpolating between range images - Chen and Williams, View Interpolation, 1993 - Shade et al. Learn how image interpolation works behind the scenes with nearest-neighbor, bilinear, and bicubic algorithms. An example of cubic interpolation is given in Fig. It outlines seven broad types of computer-assisted operations, including image rectification and restoration, image enhancement, image classification, data merging and GIS integration, hyperspectral image analysis, biophysical modeling 1. Authors: Dhruv Mahajan (Columbia University) Fu-Chung Huang (UC Berkeley) Wojciech Matusik (Adobe Systems) Feb 5, 2021 · This depends on the image interpolation algorithms in use by the combination of PowerPoint, your graphics card and the projector. PRE-PROCESING. The idea of this project is to Oct 12, 2014 · Moving Gradients: A Path-Based Method for Plausible Image Interpolation. txt) or view presentation slides online. SlideServe has a very huge collection of Tutorials image interpolation PowerPoint presentations. The document provides examples of Jul 30, 2014 · Image Interpolation. These techniques are gaining importance due to their application When generalizing cubic interpolation to two dimensions we need 16 samples in the image (a \ (4\times4\) subgrid). There are three main types of interpolation used for resizing images: nearest neighbor, bilinear, and bicubic. Signals and image processing by computer Winter 2012-13 Yael Erez. Description of Problem Examples One-Dimensional Signals Two-Dimensional Images This document discusses various digital image processing techniques including zooming, shrinking, pixel relationships, and distance measures. While downloading, if for some reason you are not able to download a presentation, the Mar 12, 2019 · Patch-based Image Interpolation: Algorithms and Applications. The importance of Use Newton’s interpolation formula and generate the divided differences (from the bottom up) “in place” in single array of dim n+1 that originally contains the function values. WHAT IS INTERPOLATION?. 2. Feb 25, 2013 · Kronecker Products-based Regularized Image Interpolation Techniques. Introduction Basic Concept of Interpolation Conventional Interpolation Previous Adaptive Linear Interpolation Proposed Method Example of Proposed Method Simulation Results Conclusions. There are 26 slide sets in both Adobe Acrobat (. of CSEE West Virginia University. Bicubic Jan 2, 2025 · Learn about interpolation, Lagrange polynomial, medical image processing, image interpolation, MATLAB examples, pixel intensity in images, and more. Alex Yin, Sayuri Soejima, Simon Yang. The document compares different 3D interpolation methods for digital images. Interpolation CS 205A: Mathematical Methods for Robotics, Vision, and Graphics Bilinear interpolation Linear interpolation is for 1D sequences—what about images? Bilinear interp. Explore how these approaches can enhance image quality and reduce noise. It describes nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation. edu Image Interpolation - Free download as Powerpoint Presentation (. It happens anytime you resize or remap (distort) your image from one pixel grid to another. May 17, 2025 · Learn about Arithmetic and Geometric Transformations, such as addition, subtraction, geometric transformations, forward and inverse mapping, interpolation techniques, and image registration concepts in digital image processing. Common applications include construction of mosaics, geographical mapping, stereo and video. For 2D functions we can also use nearest neighbor, cubic and spline interpolation. It explores both equally and unequally spaced intervals, emphasizing the importance of selecting appropriate formulas based on data positioning. The history of CT algorithms includes significant advancements from back projection techniques to iterative reconstruction methods, which have improved image quality while allowing for lower radiation Jul 30, 2014 · An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Given the pixels of I[n; m] at integer values of m and n, it computes the pixel at a non-integer position I(v; u) as: Quick Examples and Basic Concept of Image Interpolation (Nearest neighbor, linear and bilinear) Interpolation is a powerful mathematical technique used to estimate unknown values that fall within a range of known data points. The document provides an overview of image reconstruction in computed tomography (CT), detailing its history, technological advancements, and the image formation process. Source:Computer Standards & Interfaces 31 (2009) 465–470 Authors:Ki-Hyun Jung & Kee-Young Yoo Speaker:Jiun-Lwen Liang Date:2012/05/22. stanford. IMAGE: STORAGE Title: Pixel Interpolation 1 Pixel Interpolation By Mieng Phu Supervisor Peter Tischer 2 Outline Pixel Interpolation and Background Scenarios Interpolation Techniques Test Data Results and Discussions Future Work Summary 3 Pixel Interpolation Predicting/interpolating missing values occurs in many areas of image processing, especially in lossless image coding. ” -Chuck Reid. Separable Interpolation Kernels Shannon Kernel Interpolation is a technique used in image resizing, zooming, shrinking, rotating, and geometric corrections. Thus, cubic interpolation uses third-order polynomials to get the “continuous” image. Image Interpolation Given the samples \ (F\) of an image \ (f\) the task of interpolation is to calculate a value for \ (f (x,y)\) even for those \ ( (x,y)\) that are not sample points. Various matlab techniques are discussed. Additionally, it covers The document discusses image reconstruction in computed tomography (CT), detailing its invention, the evolution through various generations, and the fundamental principles behind CT imaging. It uses piecewise polynomials, typically cubic polynomials, to fit curves to these data points. Computed tomography (CT) image reconstruction involves estimating digital images from measured x-ray projection data. Preprocessing operations Pre-processing aims to correct degradations by using prior knowledge about the degradation, image acquisition device, or objects in the image. Image Interpolation • Introduction - What is image interpolation? - Why do we need it? • Interpolation Techniques - 1D 1. 55. Nearest neighbor considers only the closest pixel, while bilinear takes the average of the closest 2x2 pixels. ppt from EE 5356 at University of Texas, Arlington. This document is related to image interpolation. Common pre-processing methods include brightness and geometric transformations as well as brightness interpolation when re-sampling images. … This document provides an introduction to digital image interpretation. Blas Trigueros (presenter) Ricardo H. Data hiding method using image interpolation. Nearest neighbor is the simplest but produces the lowest quality, while bicubic is the most complex but highest quality. It has advantages over other interpolation methods like bilinear and bicubic in terms of speed and reducing artifacts like aliasing, blurring, and edge halos through adaptive Explore concepts of data interpolation, image resizing methods, general interpolation functions, enlargement by spatial filtering, scaling smaller images, and techniques for image rotation and anamorphosis. Jan 8, 2025 · Uncover the intricate world of digital imaging, including HVS operation, intensity levels, illumination models, and image interpolation techniques. UNIT-V IMAGE-BASED RENDERING AND RECOGNITION View interpolation - Layered depth images - Light fields and Lumigraphs - Environment mattes - Video-based rendering -Object detection - Face recognition - Instance recognition Category recognition - Context and scene understanding - Recognition databases and test sets. HPEC 2009 Workshop. It explains the importance of spatial and gray level resolution in images, detailing how they affect image quality in Truncation Error in Image Interpolation Loc Simon SampTA 2013 - Bremen 1 Collaborator Jean-Michel Morel 2 Truncation error: What is that? X k s X t s 3 Truncation error: What is that? Transcript and Presenter's Notes Title: Image Interpolation Methods using E-spline 1 Image Interpolation Methods using E-spline View Different image interpolation schemes PowerPoint (PPT) presentations online in SlideServe. is one way to generalize linear interpolation to 2D No. Circular interpolation allows curved tool paths but is limited to 2 axes. Source: IEEE Transcation on Information Forensics and Security, Vol. ALGORITHM -A SET OF RULES OR DIRECTIONS FOR GETTING SPECIFIC OUTPUT FROM SPECIFIC INPUT. It covers essential concepts such as color fundamentals, color models (RGB, CMY, CMYK, HSI), full-color image processing techniques, and pseudo color image processing, explaining how colors are perceived and manipulated in both digital and printed media. Spline interpolation is a technique for generating new data points within the range of a discrete set of known data points. It introduces Joseph-Louis Lagrange, who developed the method. It covers statistical concepts like normal distribution and linear regression methods for fitting straight lines. Typical ranges of • It is a discrete point-sampling of a continuous function • If we could somehow reconstruct the original function, any new image could be generated, at any resolution and scale Adapted from: S. CEDCT is based on Lie groups and can be applied for 2D and 3D image and data interpolation. In this blog, we will discuss the Nearest Neighbour, a non-adaptive interpolation method in detail. Presentation Outline. How can we generate a half-sized version? Source: S. Seitz Upsampling This image is too small for this screen: How can we make it 10 times as big? Simplest approach: repeat each row and column 10 times (“Nearest neighbor interpolation”) Image interpolation Recall how a digital image is formed It is a discrete point See full list on graphics. INTERPOLANTS. Parametric interpolation, including NURBS, generates points directly on the The document describes the CEDCT (Continuous Extension of the Discrete Orbit Function Transform) interpolation algorithm. Nov 27, 2014 · Image Interpolation. Interpolation can be used to modify the number of and locations of the samples. Image Scaling Last time: This image is too big to fit on the screen. It also describes digitizers, different types of digital storage, and principal display devices. Seitz Upsampling This image is too small for this screen: How can we make it 10 times as big? Simplest approach: repeat each row and column 10 times (“Nearest neighbor interpolation”) Image interpolation Recall how a digital image is formed It is a discrete point Sep 15, 2014 · Edge-Directed Image Interpolation. Learn about reconstructing images at different resolutions and scales. By employing interpolation methods, presenters can fill in gaps in their datasets, allowing The document discusses extrapolation and interpolation as statistical techniques used to predict and estimate data points beyond or between known values. These methods apply spatial or frequency domain filters to The document presents the fundamentals of digital image processing, covering image sensing and acquisition methodologies, including single, line, and array sensors, as well as techniques for sampling and quantization necessary to convert continuous images into digital format. For band-limited images indeed such a unique The document discusses various interpolation methods used in CNC machining, including linear, circular, and parametric interpolation. Where Does Patch Come from?. The document provides the Lagrange interpolation formula and shows an example of using it. The topics covered include: Image Enhancement by Point The document discusses key concepts in image processing including image sensing, acquisition, formation, sampling, quantization, and digital representation. Key methods discussed include simple back projection This document discusses digital image processing. The document discusses linear and quadratic spline interpolation and provides an example of using quadratic splines to interpolate the velocity of a rocket at different times The document discusses the key components of an image processing system, including image sensing, digitization, storage, and display. , f(x), 0 < x < 1. Lagrange interpolation polynomials are also covered, which avoid divided differences by reformulating Newton's method. It discusses what digital images are, how they can be displayed in color composites, and how surface features typically appear on true and false color composites. Do. Examples and implementation techniques using MATLAB are also provided to better understand these methods. pdf), Text File (. Nickolaus Mueller, Yue Lu, and Minh N. Outline of the Talk. “In theory, there is no difference between theory and practice; In practice, there is. The weights depend on the relative positions of the original This document discusses various interpolation methods used in numerical analysis and civil engineering. Seitz Image interpolation d = 1 in this example Recall how a digital image is formed • It is a discrete point-sampling of a continuous function The document discusses Lagrange interpolation, a polynomial interpolation method. pptx) format. IMAGE-BASED RENDERING AND RECOGNITION Over the last few decades, image-based The difference between interpolation and super resolution Interpolation only involves upsampling the low-resolution image, which is often assumed to be aliased due to direct down-sampling. Neuroscience: receptive fields of neighboring cells in human vision system have severe overlapping Interpolation Taking advantage of hardware Graphics hardware Compression hardware Implementations Lightfields, SIGGRAPH 96, Levoy and Hanrahan Lumigraphs, SIGGRAPH 96, Gortler et al. By: Mieng Phu Supervisor: Peter Tischer. 2 Quadratic Interpolation/ If three data points are available, the estimate is improved by introducing some curvature into the line Jul 24, 2014 · Reversible Image Watermarking Using Interpolation Technique . It describes how the human eye forms images and contains photoreceptor cells. Master the science of digital image processing with practical examples. 1 Newton’s Divided-Difference Interpolating Polynomials Linear Interpolation/ Is the simplest form of interpolation, connecting two data points with a straight line. Jun 24, 2012 · Bi-linear Interpolation • Distance-weighted average of DN values of the closest 4 pixels • Advantage output image is smoother than the nearest neighbor method • Disadvantage alters the original DN values This document discusses digital image processing concepts including: - Image acquisition and representation, including sampling and quantization of images. This document discusses different interpolation techniques used in digital image processing. DETECTORS. Understand the importance of interpolating surrounding values to enhance image quality. Super resolution aims to address undesirable effects, including the resolution degradation, blur and noise effects. REFORMATTED RAW DATA. Mar 1, 2025 · Explore various techniques in orthographic projection for finding ray starting points, casting rays, and image interpolation along with linear and trilinear methods. Download presentation by click this link. Gain insights into sensor noise reduction and image enhancement methods. ALGORITHM MUST TERMINATE AFTER FINATE NUMBER OF STEPS . It notes that while linear interpolation is simple, it results in faceted tool paths and reduced accuracy. What is pixel interpolation?. EE465: Introduction to Digital Image Processing introduces interpolation techniques. It discusses how these resolutions affect image quality and introduces common image file formats. SlideServe has a very huge collection of Different image interpolation schemes PowerPoint presentations. Figure 18. Additionally, it highlights the importance of pixel adjacency and edge detection in image analysis. Dec 30, 2012 · IMAGE RECONSTRUCTION. , Layered Depth Images, 1998 2. Dec 20, 2019 · INTERPOLATION. Both methods are essential in various fields such as Widely used in graphics: image, texture, noise, animation, curves and surfaces Nearest neighbor, bilinear, cubic interpolation Basis functions Square Triangle Hermite (smooth) Image-Based Rendering View Interpolation 1. Modern commercial CT scanners use analytical methods like filtered back projection or Fourier filtering to reduce blurring. The three most common zooming methods in image processing are the following: Pixel replication or nearest neighbor interpolation Zero-order hold method Zooming K times Nov 11, 2014 · Chapter 3. f1(x) designates that this is a first-order interpolating polynomial. - A simple image formation model where the intensity of a pixel is a function of illumination and reflectance at that point. It means to enlarge an image to make the details of that image clearer and more visible. It covers common image sensing devices like cameras, scanners, and MRI systems. Introduction to Image Processing Goal of image processing? Improve image quality, save memory/storage using compression Related areas and applications of image processing Computer vision, Computer graphics, many applications. Main steps of image formation? Interpolation - Free download as Powerpoint Presentation (. This document discusses interpolation methods for estimating values of a function between given points, focusing on techniques like Newton's forward and backward interpolation, Lagrange's method, and spline interpolation. The function then can be utilized to approximate the data values at intermediate points. Jan 3, 2025 · Understand how to generate smaller or larger versions of images through interpolation techniques, including nearest-neighbor, linear, and bicubic interpolation. Xin Li Lane Dept. Moving Gradients: A Path-Based Method for Plausible Image Interpolation. Jan 4, 2025 · This chapter discusses curve fitting approaches such as least-squares regression and interpolation. Outline . They are quite large because of the images in them. View image_interpolation. What is pixel interpolation? Applications Project Aims Lossless Image Processing Image and Video Processing Methodology Work so far achieved Summary. It also outlines the main steps in digital image processing, including preprocessing, enhancement, transformation, and classification. Finally, it discusses concepts like spatial and gray-level resolution, sampling and . Unstructured lumigraphs, SIGGRAPH 01, Buehler et al. Problem Formulation. It discusses nearest neighbor, tri-linear, cubic-keys, Catmull-Rom spline, clamped cubic spline, and B-spline interpolation methods. Extrapolation involves extending trends observed in existing data to make predictions about future values, while interpolation estimates values within the range of known data points. Given an image, can interpolation be detected? If so, can the interpolation rate be determined? The Concept A interpolated sample is a linear combination of neighboring original samples y(n0). 5, No. ppt), PDF File (. It defines digital image processing as the computer-based manipulation and interpretation of digital images. It also discusses inverse Jul 13, 2014 · Least-Squares Warped Distance for Adaptive Linear Image Interpolation. The document provides detailed Computed tomography (CT) reconstructs 2D or 3D images of internal structures from collected data, utilizing a process that includes data acquisition, image reconstruction, and image display. Bilinear interpolation method Bilinear interpolation is accomplished by the following equation: Bilinear interpolation is the most complex, slowest, but has the best results * The constants, ki , are different than the constants used in the spatial mapping equations The four unknown constants are found by using the four surrounding points shown Simplest approach: repeat each row and column 10 times (“Nearest neighbor interpolation”) Image interpolation Recall how a digital image is formed It is a discrete point-sampling of a continuous function If we could somehow reconstruct the original function, any new image could be generated, at any resolution and scale 1 2 3 4 5 Adapted 22 Image interpolation Recall that a digital images is formed as follows: d = 1 in this example 1 2 3 4 5 Recall that a digital images is formed as follows: It is a discrete point-sampling of a continuous function If we could somehow reconstruct the original function, any new image could be generated, at any resolution and scale Adapted from: S Figure 18. Nearest neighbor assigns pixel values by finding the closest pixel in the original image, while bilinear interpolation uses weighted averages DIGITAL IMAGE INTERPOLATION Image interpolation occurs in all digital photos at some stage — whether this be in bayer demosaicing or in photo enlargement. Digital image concepts and interpolation techniques for optical and digital zoom are discussed. One step beyond bilinear by considering the closest 4x4 neighborhood of known pixels, for a total of 16 pixels Since these are at various distances from the unknown pixel, closer pixels are given a higher weighting in the calculation Produces sharper images than the previous two methods. 1, March 2010 Authors: Lixin Luo , Zhenyong Chen, Ming Chen, Xiao Zeng and Zhang Xiong Speaker: Hon- Hang Chang Slideshow 2291656 by xanto Linear Interpolation Given a function defined at two points, f(0), f(1), we want to find values for intermediate points, eg. - Download as a PPT, PDF or view online for free The document covers key concepts in digital image processing, including spatial and intensity resolution, aliasing, and image interpolation techniques. It covers technical aspects such as algorithms, convolution, interpolation, and different methods of image reconstruction including back projection, iterative, and analytical methods. Introduction What is image interpolation? Why do we need it? Interpolation Techniques 1D zero-order, first-order, third-order 2D zero-order, first-order, third-order Directional interpolation* Interpolation Applications Digital zooming (resolution enhancement) Image Scaling Last time: This image is too big to fit on the screen. Jun 24, 2012 · Bi-linear Interpolation • Distance-weighted average of DN values of the closest 4 pixels • Advantage output image is smoother than the nearest neighbor method • Disadvantage alters the original DN values • It is a discrete point-sampling of a continuous function • If we could somehow reconstruct the original function, any new image could be generated, at any resolution and scale Adapted from: S. There are different types of interpolation including nearest neighbor, bilinear, and bicubic. This article discusses the concept of interpolation and extrapolation, and how these techniques can be applied to 2D images. Image resizing is necessary when you need to increase or decrease the total number of pixels, whereas remapping can occur under a wider variety of Nov 1, 2014 · In current digital era the image interpolation techniques based on multi-resolution technique are being discovered and developed. It outlines various generations of CT scanners, reconstruction techniques, and mathematical algorithms, emphasizing the importance of image quality and radiation dose. Optical zoom uses lens magnification before sensing, whereas digital Different types of rendering using different amounts of geometry Interpolation Morphing interpolating texture map and shape Generation of a new image is independent of scene complexity Morph adjacent images to view between based on viewpoints being closely spaced Uses camera position, orientation and range to deteremine pixel by pixel Images The Problem An image consists of a number of discrete samples. Early methods included back projection, which was simple but produced blurred images. Sampling converts a continuous image to digital by selecting pixel values at regular Image Interpolation PPT - Free download as Powerpoint Presentation (. CONVOLUTION WITH FILTER. Image Interpolation. Correspondences and epipolar analysis - Laveau and Faugeras, Collection of Images, 1994 - McMillan and Bishop, Plenoptic Modeling, 1995 3. ppt / . this is used to modify image size. Light Field Rendering Capture: Computer-controlled camera rig Move camera to grid of locations on a plane Sep 8, 2005 · Abstract Geometric transformations are widely used for image registration and the removal of geometric distortion. It also discusses inverse The function compute pixel performs image interpolation. pptx), PDF File (. Read about bilinear interpolation. Sep 1, 2012 · Pixel Interpolation. Sampled Image: Reconstructed image by interpolation:. Polynomials are the most common choice of interpolants because they are easy to: Evaluate, Besides its poor behavior to interpolate high frequencies, linear interpolation has another significant disadvantage: the interpolated curve is not continuous in its first derivative at the grid points. wjinpu jacgy gkttq krkcmq uvrq jzxrkg bicassc mbnw zsikqlkd jfcql oil ogycm griiiq jgt jxei