Image interpolation by adaptive 2-D autoregressive modeling

Vinit Jakhetiya; Ashok Kumar; Anil Kumar Tiwari

doi:10.1117/12.855785

26 February 2010 Image interpolation by adaptive 2-D autoregressive modeling

Vinit Jakhetiya, Ashok Kumar, Anil Kumar Tiwari

Proceedings Volume 7546, Second International Conference on Digital Image Processing; 75461J (2010) https://doi.org/10.1117/12.855785
Event: Second International Conference on Digital Image Processing, 2010, Singapore, Singapore

Abstract

This paper presents a new interpolation algorithm based on the adaptive 2-D autoregressive modeling. The algorithm uses a piece-wise autoregressive (PAR) model to predict the unknown pixels of high resolution image. For this purpose, we used a block-based prediction model to predict the unknown pixels. The unknown pixels are categorized into three categories and they are predicted using predictors of different structure and order. Prediction accuracy and the visual quality of the interpolated image depend on the size of the window. We experimentally found an appropriate window size and have shown that subjective as well as objective (PSNR) quality of the high resolution (HR) images is same, on an average, as that of the competitive such method reported in literature and also the method is a single pass.

Citation Download Citation

Vinit Jakhetiya, Ashok Kumar, and Anil Kumar Tiwari "Image interpolation by adaptive 2-D autoregressive modeling", Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75461J (26 February 2010); https://doi.org/10.1117/12.855785

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available