Composite high frequency predictive scheme for efficient 2-D up-scaling performance

Abstract

This paper presents a new composite scheme to tackle the non-uniform blurring that arises because of image up-scaling. The image up-scaling results in undesirable blurring artifacts at the edge and fast changing regions due to high frequency (HF) and very high frequency (VHF) degradation. Most of the widely used interpolation schemes fail to predict the HF information in up-scaled image which consequently results in undesirable blurring. In order to overcome this problem, the proposed composite scheme is developed by combining a pre-processing and a post-processing operation to efficiently restore HF and VHF information in the up-scaled image. The pre-processing operation makes use of an iterative global sharpening scheme prior to image up-scaling to boost up the high frequency information so as to alleviate the extent of blurring in the up-scaled images. The post-processing scheme is operated on the up-scaled images to enhance and predict the HF information using a local statistics based local adaptive Laplacian filter. The appropriate fusion of pre-processing and post-processing operations results in more accurate prediction of HF in the up-scaled images. Experimental results reveal that the proposed composite scheme gives much less blurring in comparison to the standalone schemes and outperform most of the widely used interpolation schemes in terms of objective and subjective measures.