Skip to main content
Log in

Adaptive Least Squares Interpolation of Infrared Images

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

This paper presents an adaptive block-by-block least squares (LS) algorithm for the interpolation of infrared (IR) images. The suggested algorithm is based on the segmentation of the low resolution (LR) image into overlapping blocks and the interpolation of each block, separately. The purpose of the overlapping is to avoid edge effects between blocks. An iterative implementation of the proposed algorithm, which considers the image acquisition model, is used for the minimization of the estimation error in each block. A weight matrix of moderate dimensions is estimated in a small number of iterations to interpolate each block. This proposed algorithm avoids the large computational complexity resulting from the matrices of large dimensions required to interpolate the image as a whole. The performance of the proposed algorithm is compared with the standard as well as the warped distance optimal interpolation of maximal order with minimal support (O-MOMS) algorithm from the peak signal-to-noise ratio (PSNR) point of view. Numerical results reveal the superiority of the proposed LS algorithm to the cubic O-MOMS algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. T. Blu, P. Thevenaz, M. Unser, MOMS: Maximal-order interpolation of minimal support. IEEE Trans. Image Process. 10(7), 1069–1080 (2001)

    Article  MATH  Google Scholar 

  2. T. Chen, H.R. Wu, B. Qiu, Image interpolation using across-scale pixel correlation, in Proceedings of ICASSP (2001)

  3. S.E. El-Khamy, M.M. Hadhoud, M.I. Dessouky, F.E. Abd El-Samie, Adaptive image interpolation based on local activity levels, in Proceedings of the National Radio Science Conference of Egypt, 2003

    Google Scholar 

  4. S.E. El-Khamy, M.M. Hadhoud, M.I. Dessouky, B.M. Salam, F.E. Abd El-Samie, A new edge preserving pixel-by-pixel (PBP) cubic image interpolation approach, in Proceedings of the National Radio Science Conference of Egypt, 2004

    Google Scholar 

  5. S.E. El-Khamy, M.M. Hadhoud, M.I. Dessouky, B.M. Salam, F.E. Abd El-Samie, Optimization of image interpolation as an inverse problem using the LMMSE algorithm, in Proceedings of IEEE MELECON, 2004

    Google Scholar 

  6. S.E. El-Khamy, M.M. Hadhoud, M.I. Dessouky, B.M. Salam, F.E. Abd El-Samie, Sectioned implementation of regularized image interpolation, in Proceedings of 46th IEEE MWSCAS, 2003

    Google Scholar 

  7. J.K. Han, H.M. Kim, Modified cubic convolution scaler with minimum loss of information. Opt. Eng. 40(4), 540–546 (2001)

    Article  MathSciNet  Google Scholar 

  8. H.S. Hou, H.C. Andrews, Cubic spline ror image interpolation and digital filtering. IEEE Trans. Acoust. Speech Signal Process. ASSP-26(9), 508–517 (1978)

    Google Scholar 

  9. W.Y. V Leung, P.J. Bones, Statistical interpolation of sampled images. Opt. Eng. 40(4), 547–553 (2001)

    Article  Google Scholar 

  10. G. Ramponi, Warped distance for space variant linear image interpolation. IEEE Trans. Image Process. 8, 629–639 (1999)

    Article  Google Scholar 

  11. J.H. Shin, J.H. Jung, J.K. Paik, Regularized iterative image interpolation and its application to spatially scalable coding. IEEE Trans. Consum. Electron. 44(3), 1042–1047 (1998)

    Article  Google Scholar 

  12. P. Thevenaz, T. Blu, M. Unser, Interpolation revisited. IEEE Trans. Med. Imaging 19(7), 739–758 (2000)

    Article  Google Scholar 

  13. M. Unser, Splines: a perfect fit for signal and image processing. IEEE Signal Processing Magazine (1999)

  14. M. Unser, A. Aldroubi, M. Eden, B-spline signal processing: Part I—Theory. IEEE Trans. Signal Process. 41(2), 821–833 (1993)

    Article  MATH  Google Scholar 

  15. M. Unser, A. Aldroubi, M. Eden, B-spline signal processing: Part II—Efficient design and applications. IEEE Trans. Signal Process. 41(2), 834–848 (1993)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to F. E. Abd El-Samie.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ashiba, H.I., Awadalla, K.H., El-Halfawy, S.M. et al. Adaptive Least Squares Interpolation of Infrared Images. Circuits Syst Signal Process 30, 543–551 (2011). https://doi.org/10.1007/s00034-010-9243-z

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-010-9243-z

Keywords

Navigation