Slant Transformation as a Tool for Pre-processing in Image Processing

The Slantlet Transform (SLT) is a recently developed multiresolution technique especially well-suited for piecewise linear data. The Slantlet transform is an orthogonal Discrete Wavelet Transform (DWT) with 2 zero moments and with improved time localization. It also retains the basic characteristics of the usual filterbank such as octave band characteristic and a scale dilation factor of two. However, the Slantlet transform is based on the principle of designing different filters for different scales unlike iterated filterbank approaches for the DWT. In the proposed system, Slantlet transform is implemented and used in Compression and Denoising of various input images. The performance of Slantlet Transform in terms of Compression Ratio (CR), Reconstruction Ratio (RR) and Peak-Signal-to-Noise-Ratio (PSNR) present in the reconstructed images is evaluated. Simulation results are discussed to demonstrate the effectiveness of the proposed method.