Certain investigation on hybrid dwt lifting scheme for image compression using cordic enhanced operation

Abstract

Images play an important role in our day to day life. Due to the newlineincreasing popularity of digital information, image compression has become newlinean extremely valuable technology. It is commonly used in multimedia newlineapplications to reduce the storage cost and provide better quality of image. newlineImage compression is a process that involves removing or reducing the newlineamount of data that is required to create a usable image. This process is newlineusually carried out by removing non-important data. Usually, an image newlineconsists of higher and lower frequency elements. The lower frequency newlineelement implies inexact information and higher frequency implies newlinecomprehensive information such as textures and edges. newlineThere are different techniques used to compress the image. Discrete newlinewavelet transform (DWT) is one of the welland#8208;adopted transforming methods newlineexploited for compressing images. This thesis, introduces a novel image newlinecompression scheme by the Adaptive Discrete Wavelet Transform-Lifting newlineScheme(ADWT-LS) model. Usually, the lifting model requires specific newlineadders and multipliers and thus, it can minimize the computational newlinecomplexity. The most important aspect of the adopted lifting-DWT scheme is newlinea novel lifting factorization that insisted on the fine-tuned constraint. The newlineLioness Integrated-Whale Optimization Algorithm approach is deployed for newlineoptimal tuning of the filter coefficient. New methods are required since each newlineapplication requires different strategy of image compression. Some can be newlinelossy and others can be lossless. In this thesis the compression is lossy and newlinebetter result is obtained by altering the parameter (filter coefficient). newline newline