DIRECTIONALLY ADAPTIVE SUPER-RESOLUTION


Turgay E., AKAR G.

16th IEEE International Conference on Image Processing, Cairo, Egypt, 7 - 10 November 2009, pp.1201-1202 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icip.2009.5413662
  • City: Cairo
  • Country: Egypt
  • Page Numbers: pp.1201-1202
  • Keywords: Maximum a-posteriori, gradient, directional regularization, edge preservation, super-resolution, RESOLUTION
  • Middle East Technical University Affiliated: Yes

Abstract

In this paper a novel direction adaptive super-resolution (SR) image reconstruction method is proposed. The proposed maximum a-posteriori (MAP) based estimator uses gradient direction for optimal noise reduction while preserving the edges. Compared to the other edge-preserving methods, the proposed algorithm uses gradient direction in addition to the gradient amplitude for optimum regularization. The method comprises a gradient amplitude and direction estimation stage where a gradient direction map is obtained. This map guides the SR reconstruction stage through iterations. Three variations of the proposed method are compared against other edge-preserving super resolution methods. PSNR (Peak signal-to-noise-ratio), SSIM (Structural similarity index measure) values, and illustrations show that the proposed method has better performance especially on image pixel values where a strong gradient is present.