Lifting scheme is a fastest efficient method to compute second generation wavelet transforms. It does not require any auxiliary memory instead original image is replaced by its wavelet transform there by giving in-place computation of the wavelet transform. Lifting scheme deals with spatial domain, which does not require the knowledge of Fourier Transform for calculating wavelet transform. In this paper, an effort has been placed on exhaustive experimentation for lifting Haar wavelet. In this proposed work, four distinct lifting schemes are applied on skin cancer medical images for better representation. The Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Compression Ratio (CR) are computed for validating the proposed work. Here, lifting scheme case 2 gives better CR than lifting scheme case 1, 3 and 4. Lifting scheme case 2 results are also better than Discrete Wavelet Transform (DWT) based Haar and Biorthogonal wavelets.

Haar Wavelet, Lifting Scheme, MSE, PSNR, SSIM, Thresholding.