Super-Resolution Using Edge Modification through Stationary Wavelet Transform
Fahim Arif, Tabinda Sarwar · 2014
In this paper, a super-resolution technique is proposed that uses a combination of bicubic interpolation and wavelet transform. Bicubic interpolation produces a high resolution image but is prone to blurring artifact. So the blurring artifact is reduced in the wavelet domain. The input low-resolution is up-sampled using bicubic interpolation. The edges of the resultant high-resolution image are enhanced using stationary wavelet transform (SWT). SWT is applied to the image to produce sub-bands of the image and then these sub-bands are modified by multiplying with a boost value. Then these sub-bands are combined using inverse stationary wavelet transform (ISWT) to produce the final high-resolution image. The quantitative and qualitative analysis illustrate that the proposed technique is provides superior results as compared to other existing techniques.