Image interpolation using shearlet based iterative refinement

Lakshman, H.; Lim, W.-Q; Schwarz, H.; Marpe, D.; Kutyniok, Gitta und Wiegand, T. (August 2015): Image interpolation using shearlet based iterative refinement. In: Signal Processing: Image Communication, Vol. 36: pp. 83-94

Abstract

This paper proposes an image interpolation algorithm exploiting sparse representation for natural images. It involves three main steps: (a) obtaining an initial estimate of the high resolution image using FIR filtering, (b) promoting sparsity in a selected dictionary through hard thresholding to obtain an approximation, and (c) extracting high frequency information from the approximation to refine the initial estimate. For the sparse modeling, a shearlet dictionary is chosen to yield a multiscale directional representation. The proposed algorithm is compared to several state-of-the-art methods to assess its objective and subjective performance. Compared to the cubic spline interpolation method, an average PSNR gain of around 0.8 dB is observed over a dataset of 200 images.

• Item Type: Journal article
• Faculties: Mathematics, Computer Science and Statistics > Mathematics > Bavarian Chair for Mathematical Foundations of Artificial Intelligence
• Subjects: 500 Science > 510 Mathematics
• ISSN: 09235965
• Language: English