Paper Info
Title
Image super resolution using interpolation and edge extraction in wavelet transform space.
Abstract
A novel approach in image enhancement is proposed. In contrast to other state-of-art algorithms, the designed technique is based on additional edges preservation procedure and mutual interpolation between the high frequency (HF) sub-band image performed via the discrete wavelet transform (DWT) and the input low resolution (LR) image. Finally, all sub-band images are combined to generate a new high-resolution (HR) image via Inverse DWT (IDWT). Numerous simulation results confirm that novel super resolution framework performs well in terms of objective criteria (PSNR, MAE and SSIM) and the more subjective measure of human vision in the different images, improving resolution sufficiently better than do existing methods.
Year
DOI
Venue
2012
10.1109/ICEEE.2012.6421202
CCE
Keywords
Field
DocType
discrete wavelet transforms,edge detection,image enhancement,image resolution,interpolation,inverse transforms,IDWT,LR image,MAE,PSNR,SSIM,discrete wavelet transform,edge extraction,edge preservation procedure,high frequency subband image,high-resolution image,human vision,image enhancement,image super resolution framework,interpolation,inverse DWT,low resolution image,mutual interpolation,state-of-art algorithms,wavelet transform space,Discrete Wavelet Transform Interpolation,Edge Extraction and Super Resolution
Top-hat transform,Computer vision,Mathematical optimization,Image fusion,Computer science,Second-generation wavelet transform,Discrete wavelet transform,Artificial intelligence,Stationary wavelet transform,Image resolution,Image scaling,Wavelet transform
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Herminio Chavez-Roman171.18
Volodymyr I. Ponomaryov212418.38
Ricardo Peralta-Fabi321.03