1 / 17

Least-Squares Warped Distance for Adaptive Linear Image Interpolation

Least-Squares Warped Distance for Adaptive Linear Image Interpolation. Presentation Outline. Introduction Basic Concept of Interpolation Conventional Interpolation Previous Adaptive Linear Interpolation Proposed Method Example of Proposed Method Simulation Results Conclusions.

tymon
Download Presentation

Least-Squares Warped Distance for Adaptive Linear Image Interpolation

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. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Least-Squares Warped Distance for Adaptive Linear Image Interpolation

  2. Presentation Outline • Introduction • Basic Concept of Interpolation • Conventional Interpolation • Previous Adaptive Linear Interpolation • Proposed Method • Example of Proposed Method • Simulation Results • Conclusions

  3. Introduction • Image interpolation plays a key role in the image processing literature • Image resizing/rotation/warping/morphing • Image/video compression • Mosaicking color filter array in DSC • De-interlacing in DTV • Lifting-based wavelet transform • Timing recovery in a digital modem • Sample rate converter • Adaptive image interpolation can provide a substantial gain in image quality. • Especially, warped distance (WaDi) approach

  4. Basic Concept of Interpolation • With given discrete samples f (xk),generating continuous function as follows • The ideal kernel is the sinc function Interpolation Kernel

  5. Conventional Interpolation -1 1 • Linear

  6. Conventional Interpolation • Keys’ Cubic Convolution Interpolation 1 -1 -2 2

  7. Previous Adaptive Linear Interpolation • Warped Distance Linear Interpolation • Definition of warped distance as follows • Note that • The variable A is a pixel-based parameter • The variable k is an image-based parameter(k = 8 fixed for the Lena image)

  8. Proposed Method • New WaDi a for a given distance s • Use distance s as a pixel-based parameter • Introduce a system to calculate s • Including low pass filter and MMSE

  9. Proposed Method • Generic diagram

  10. Proposed Method • Systematic approach to employ the least-squares technique

  11. Example of Proposed Method • Low complexity version • Apply 3-tap low pass filter gi= 1/2{s, 1, 1-s} • Define cost function as follows

  12. Example of Proposed Method • Get a to minimize the cost as follows • We have where

  13. Simulation • Two scenarios to evaluate the methods • One is a decimation-interpolation simulation • Filtered followed by down-sampler with a factor of two • Interpolate decimated image with a factor of two • The other is a rotation test • Fifteen rotations performed successively • Rotate by 24 degree for each rotation

  14. Simulation Results for DI Test • PSNR resulting from the decimation-interpolation test

  15. Simulation Results (DI Test)

  16. Simulation Results (Rotation Test)

  17. Conclusions • A Pixel-based adaptive linear interpolation has been presented • A generic system, formulation, and its low complexity version have been proposed • Simulation results show that the proposed method • Give better visual quality • Give better objective quality in terms of PSNR • than previous methods such as conventional linear, cubic convolution, and previous warped distance-based methods

More Related