Authors:
James McAvoy
;
Ehsan Rahimi
and
Chris Joslin
Affiliation:
Carleton University, Canada
Keyword(s):
Resizing Algorithm, Image Halving and Doubling, DCT Transformation, Fixed-point integer transformation, Subband Approximation, Low-complexity.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Color and Texture Analyses
;
Computer Vision, Visualization and Computer Graphics
;
Document Imaging in Business
;
Image and Video Analysis
;
Image and Video Coding and Compression
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
Abstract:
This paper proposes an efficient image resizing algorithm, including both halving and doubling, in the DCT domain. The proposed image resizing algorithm works on a 4 by 4 DCT block framework with a lower complexity compared to the similar previous methods. Compared to the images that were halved or doubled through the bilinear interpolation, the proposed algorithm produces images with similar or higher PSNR or SSIM values at the significantly lower computational cost. The test results also confirm that our approach improves the current frequency domain resizing algorithms through the fixed-point integer transformation which reduces the computational cost by more than 60\% with negligible dB loss.