Successive Image Interpolation Using Lifting Scheme Approach

Problem statement: Fast and accurate interpolation and resizing of images and video frames is a much sought after research area in multimedia applications. The more accurate schemes are computationally expensive and require more time for execution. We proposed here Discrete Wavelet Transform (DWT) using lifting scheme as an accurate and computationally inexpensive interpolation technique for image resizing. Approach: In this study, the lifting scheme DWT algorithm was applied for interpolation of the images to the scale 2^-n for reduction in size where n indicated the level of DWT. To magnify the image to the scale 2ⁿ, IDWT was used after the zeroeth level DWT, while DWT was used for subsequent reconstruction. Results: In case of reduction in size, the DWT components were calculated to a level so that the four DWT components were reduced to single pixel size and the reconstruction is again carried out to the original size. The reconstruction results were bench marked using Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR) with other schemes like Bilinear and Bicubic interpolations. The two component Harr mother wavelet was found to be suitable for the fast computations of the interpolated images and their subsequent versions. Conclusion: It has been found that after higher level of DWT computations like 10 or 11th level, the MSE increases beyond acceptable limits and the PSNR drops below 20 dB. But the interpolation or reconstruction is completed in much less time with better MSE and PSNR as compared to the bilinear and bicubic scheme. The present technique provided fast interpolation algorithm for multimedia and video processing applications.