Paper
19 July 2013 Image super-resolution using DCT interpolation and sparse learning-based method
Saulo R. S. Reis, Graça Bressan
Author Affiliations +
Proceedings Volume 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013); 88784C (2013) https://doi.org/10.1117/12.2030721
Event: Fifth International Conference on Digital Image Processing, 2013, Beijing, China
Abstract
In this paper we present a method for single image super-resolution that use discrete cosine transform (DCT) interpolation and a sparse learning-based super-resolution method. The input low-resolution (LR) image is interpolated using both DCT interpolation and bicubic interpolation methods. The bicubic Interpolated image undergoes a process sparse coding using OMP algorithm. The obtained sparse coefficients are multiplied with high-resolution dictionary generated in the training phase, resulting in the intermediate high-resolution (HR) image. The final HR image is obtained by adding the DCT interpolated image and intermediate HR image. The experimental results demonstrate the effectiveness of the method proposed in terms of PSNR, SSIM and visual quality.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Saulo R. S. Reis and Graça Bressan "Image super-resolution using DCT interpolation and sparse learning-based method", Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88784C (19 July 2013); https://doi.org/10.1117/12.2030721
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Super resolution

Lawrencium

Image processing

Visualization

Image quality

Associative arrays

Bridges

RELATED CONTENT


Back to Top