Image Interpolation Based on 2D-DWT with Novel Regularity-Preserving Algorithm Using RLS Adaptive Filters

This paper proposes a novel method for the image interpolation problem based on two-dimensional discrete wavelet transform (DWT) with the edge preserving approach. The purpose of this method is to consider two contrasting issues of over-smoothing and creation of spurious edges at the same time, and offer a novel solution based on statistical dependencies of image sub-bands, and noise behavior. The offered method has a multi-faceted approach for the problem; by sub-band coding, it handles each 2D-DWT image sub-band with a different solution. For LH and HL sub-bands, two algorithms work together in order to preserve regularity. Area_Check algorithm is a four-phase edge-preserving algorithm that aims to recognize and interpolate separating lines of environments and edgy regions in the best possible way. On the other hand, RLS_AVG algorithm interpolates smooth surfaces of the image by keeping the regularity of the image without over-smoothing. In this regard, the offered algorithm has a great power to counter jaggies and annoying artifacts. In the end, in order to demonstrate the capability, and performance of the proposed method, the final results in various metrics are compared with the results of the most famous and the newest image interpolation methods.

Automated summary

This paper proposes a novel method for the image interpolation problem based on two-dimensional discrete wavelet transform (DWT) with the edge preserving approach. The method addresses the issues of over-smoothing and creation of spurious edges simultaneously, and offers a solution based on statistical dependencies of image sub-bands and noise behavior. The method has a multi-faceted approach for the problem, handling each 2D-DWT image sub-band differently to preserve regularity and interpolate smooth surfaces without over-smoothing, resulting in effective reduction of jaggies and annoying artifacts.