Interpolation methods for Image Transcoding Asmar Azar Khan 2005-06-0003.

Slides:



Advertisements
Similar presentations
ITK Deformable Registration
Advertisements

Gholamreza Anbarjafari, PhD Video Lecturers on Digital Image Processing Digital Image Processing Resizing Image.
Image Interpolation CS4670: Computer Vision Noah Snavely.
© by Yu Hen Hu 1 ECE533 Digital Image Processing Image Enhancement in Frequency Domain.
Prof. Brian L. Evans Dept. of Electrical and Computer Engineering The University of Texas at Austin EE445S Real-Time Digital Signal Processing Lab Spring.
MIT EECS 6.837, Durand and Cutler Sampling, Aliasing, & Mipmaps.
Digital Image Processing. 2 Interpolation of Data Suppose we have a collection of four values that we wish to enlarge to eight: Interpolated results x-axis.
1 Outline  Introduction to JEPG2000  Why another image compression technique  Features  Discrete Wavelet Transform  Wavelet transform  Wavelet implementation.
Filtering CSE P 576 Larry Zitnick
Sampling, Aliasing, & Mipmaps
Image Filtering, Part 2: Resampling Today’s readings Forsyth & Ponce, chapters Forsyth & Ponce –
Edges and Scale Today’s reading Cipolla & Gee on edge detection (available online)Cipolla & Gee on edge detection Szeliski – From Sandlot ScienceSandlot.
Lecture 2: Edge detection and resampling
Image Sampling Moire patterns
Computer Vision Introduction to Image formats, reading and writing images, and image environments Image filtering.
Lecture 4: Image Resampling CS4670: Computer Vision Noah Snavely.
Lecture 3: Image Resampling CS4670: Computer Vision Noah Snavely Nearest-neighbor interpolation Input image 3x upsample hq3x interpolation (ZSNES)
Sampling Random Signals. 2 Introduction Types of Priors Subspace priors: Smoothness priors: Stochastic priors:
Image Sampling Moire patterns -
Conference title 1 A WYNER-ZIV TO H.264 VIDEO TRANSCODER José Luis Martínez, Pedro Cuenca, Gerardo Fernández-Escribano, Francisco José Quiles and Hari.
1 Motivation Video Communication over Heterogeneous Networks –Diverse client devices –Various network connection bandwidths Limitations of Scalable Video.
Chapter 5 Frequency Domain Analysis of Systems. Consider the following CT LTI system: absolutely integrable,Assumption: the impulse response h(t) is absolutely.
IMAGE SAMPLING AND IMAGE QUANTIZATION 1. Introduction
Digital Image Processing CCS331 Image Interpolation 1.
Image Resampling CS4670: Computer Vision Noah Snavely.
Copyright ©2010, ©1999, ©1989 by Pearson Education, Inc. All rights reserved. Discrete-Time Signal Processing, Third Edition Alan V. Oppenheim Ronald W.
1 Lab. 4 Sampling and Rate Conversion  Sampling:  The Fourier transform of an impulse train is still an impulse train.  Then, x x(t) x s (t)x(nT) *
Image Resampling CS4670: Computer Vision Noah Snavely.
Image Processing Xuejin Chen Ref:
Lecture 7: Sampling Review of 2D Fourier Theory We view f(x,y) as a linear combination of complex exponentials that represent plane waves. F(u,v) describes.
Digital image processing Chapter 3. Image sampling and quantization IMAGE SAMPLING AND IMAGE QUANTIZATION 1. Introduction 2. Sampling in the two-dimensional.
Image Processing Basics. What are images? An image is a 2-d rectilinear array of pixels.
Digital Image Processing, 2nd ed. © 2002 R. C. Gonzalez & R. E. Woods Image Processing Example.
Computer Vision Spring ,-685 Instructor: S. Narasimhan Wean 5403 T-R 3:00pm – 4:20pm.
GEOMETRIC OPERATIONS. Transformations and directions Affine (linear) transformations Translation, rotation and scaling Non linear (Warping transformations)
Fundamentals of Digital Signal Processing. Fourier Transform of continuous time signals with t in sec and F in Hz (1/sec). Examples:
Midterm Presentation Performed by: Ron Amit Supervisor: Tanya Chernyakova Semester: Spring Sub-Nyquist Sampling in Ultrasound Imaging.
MIT EECS Sampling, Aliasing, & Mipmaps. MIT EECS Last Time? Global illumination “physically accurate light transport” The rendering equation.
BIEN425 – Lecture 15 By the end of this lecture, you should be able to: –Design and implement integer decimators and interpolators –Design and implement.
Brent M. Dingle, Ph.D Game Design and Development Program Mathematics, Statistics and Computer Science University of Wisconsin - Stout Image Processing.
Image Enhancement (Frequency Domain)
Computer Vision – Sampling Hanyang University Jong-Il Park.
1 Dr. Scott Schaefer Antialiasing. 2/70 What is aliasing?
CS654: Digital Image Analysis Lecture 11: Image Transforms.
Image Interpolator Supervisor By: Dr. Rajeev Srivastava Prashant Bhutani Associate Professor CSE, IIT-BHU.
2. Multirate Signals.
Antialiasing. What is alias? Alias - A false signal in telecommunication links from beats between signal frequency and sampling frequency (from dictionary.com)
Prof. Brian L. Evans Dept. of Electrical and Computer Engineering The University of Texas at Austin EE445S Real-Time Digital Signal Processing Lab Spring.
Image Resampling & Interpolation
… Sampling … … Filtering … … Reconstruction …
Design for Embedded Image Processing on FPGAs
Chapter 6: Image Geometry 6.1 Interpolation of Data
Digital Signal Processing Lecture 4 DTFT
Image Sampling Moire patterns
Chapter 3 Sampling.
How Signals are Sampled: ADC
Image Sampling Moire patterns
EEE 501 Applied Digital Image Processing Dr. Türker İnce
Samuel Cheng Slide credits: Noah Snavely
Filtering Part 2: Image Sampling
Resolution Resolution: 6 x 4.
Image Sampling Moire patterns
Comagna SIRE technology
Image Resampling & Interpolation
© 2010 Cengage Learning Engineering. All Rights Reserved.
Resampling.
Chapter 7 Finite Impulse Response(FIR) Filter Design
Chapter 3 Sampling.
Samuel Cheng Slide credits: Noah Snavely
Presentation transcript:

Interpolation methods for Image Transcoding Asmar Azar Khan

Transcoding: Scope and Application Multimedia Networks  Different Nodes  Image Resolution  Different Encoding Schemes MPEG-1 to H.261 MPEG-2 to H.263 MPEG-1 to DV

Transcoding: Scope and Application Spatial Resolution  CIF (352 x 288)  QCIF (176 x 144)  VGA (640 x 480) Mobile Devices  PDAs  Gaming Consoles

Image Scaling Filtering  Aliasing Re-sampling  Continuous Image  Sampling

Image Scaling QCIF LP-Filtering VGA M N LP-Filtering

Image Scaling QCIF Interpolator VGA Sampler

Ideal Interpolation Interpolators  Preserves high frequency  No aliasing Approximators

Nearest Neighbor Nearest Pixel Value  Less Complex  Low Quality  Edge handling

Linear Interpolation:

Bicubic Interpolation

Quadratic Interpolation

Cubic B-Spline Interpolation

Simulations and Performance Metric Fourier Analysis Pass-band Cutoff Points Stop-band Subjective/Visual Quality Interpolation Error  SNR Computational Complexity Runtime Memory Overhead

Hardware and Software Encoders in Software Memory and Processing Issues  Real time issues Hardware design  Nearest Neighbor  Bicubic Interpolation Cubic B-Spline Hardware Design  Memory Requirement  Reducing MACs  FPGA Availability

References Survey: Interpolation Methods in Medical Image Processing Thomas M. Lehmann Cubic Splines for image Interpolation and Filtering Hseih S. Hou Real-Time FPGA-Based Architecture for Bicubic Interpolation: An Application for Digital Image Scaling Marco Aurelio Nuño-Maganda, Miguel O. Arias-Estrada Cubic Convolution Interpolation for Digital Image Processing Robert g. Keys

Questions !