Paper Title
Image enhancement using second generation Wavelet transform

This paper addresses the problem of recovering a super-resolved image from a set of warped blurred and decimated versions thereof. Due to the factors like processing power limitations and channel capabilities images are often downsampled and transmitted at low bit rates resulting in a low resolution compressed image. In most digital imaging applications, HR images or videos are usually desired for later image processing and analysis. In this paper, we propose lifting schemes for intentionally introducing down sampling of the high resolution image sequence before compression and then utilize super resolution techniques for generating a HR image at the decoder.Extracting more information from multi- source images is an attractive thing in remotely sensed image processing, which is recently called the image fusion. Lifting wavelet transform has its advantages over the ordinary wavelet transform by way of reduction in memory required for its implementation. This is possible because liftingtransform uses in-place computation. The lifting coefficientsreplace the image samples present in the respective memorylocations. In our proposed approach the forward lifting isapplied to the high resolution images which are compressed using Set Partioning in Hierarchical Trees (SPHIT), thecompressed images are transmitted which results in LR images at the encoder, at the decoder superresolution techniques are applied; lifting scheme basedfusion is performed, then decoded using DSPIHT andInverse lifting is applied. Soft thresholding is usedto remove noise and theblur is removed using blind deconvolution, and finally willbe interpolated using our novel interpolation technique.We have performed bothobjective and subjective analysis of the reconstructed image,and the resultant image has better super resolution factor, anda higher ISNR and PSNR. Keywords- Super-resolution (SR), SPIHT, DSPIHT, Image Registration, Fusion, Interpolation.