Spatial resolution enhancement for astronomical images using wavelet transform techniques

This study introduces an innovative methodology for enhancing the spatial resolution of astronomical, remote sensing, and conventional images. The approach involves decomposing low-resolution (LR) image using discrete wavelet transform (DWT), followed by wavelet zero padding (WZP) to the input LR image and new edge-directed interpolation (NEDI) on high-frequency sub-bands. Additionally, a novel adaptive thresholding technique termed edge-aware thresholding (EAT) is applied on the high-frequency sub-bands; EAT utilizes the Sobel operator to detect edge pixels and enhance them; the high-resolution image is reconstructed through inverse DWT (IDWT), integrating the refined sub-bands with the zero-padded low-resolution image. This method aims to improve the clarity of low-resolution images by preserving high-frequency features of the image, such as edge and texture, while reducing edge artifacts and discontinuities caused by the transformation. This proposed technique ensures superior performance over traditional and current wavelet-based resolution enhancement techniques in terms of qualitative and quantitative measurements. Such advancement holds promise for many applications where high-detail images are crucial.