Optimized Image Scaling Using DWT and Different Interpolation Techniques

Discrete Wavelet Transform (DWT) has gained much limelight in the past years. Wavelet Transform has precedence over Discrete Fourier Transform and Discrete Cosine Transform because they capture the frequency as well as spatial information of a signal. In this paper DWT has been used for image scaling purpose. To achieve higher visual quality image, DWT is applied on the gray scale image using a downscaling technique. The original image is recovered using IDWT by employing different interpolation techniques for upscaling. In this paper interpolation techniques used are: Nearest Neighbor, Bilinear and Bicubic. Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) is calculated for quantifying interpolated image effectiveness. Results show that the reconstructed image is better when using a combination of DWT and Bicubic interpolation

@article{Aslam2016,
  title     = {Optimized Image Scaling Using DWT and Different Interpolation Techniques},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {6},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Wardah Aslam and Khurram Khurshid and Asfaq Ahmed Khan},
  doi       = {10.14569/IJACSA.2016.070638},
  url       = {https://doi.org/10.14569/IJACSA.2016.070638}
}