Low complex image resizing algorithm using fixed-point integer transformation
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.
|Keywords||DCT transformation, Doubling, Fixed-point integer transformation, Image halving, Low-complexity, Resizing algorithm, Subband approximation|
|Conference||13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018|
McAvoy, J. (James), Rahimi, E. (Ehsan), & Joslin, C. (2018). Low complex image resizing algorithm using fixed-point integer transformation. In VISIGRAPP 2018 - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (pp. 143–149).