Abstract:
With the increasing evolution of technology and digital age, the demand of multimedia products grew faster contributing to the storage of memory devices and insufficient bandwidth and resulted in the need of image compression. The look for effective picture compression strategies is yet a substantial test at the intersection of practical examination and measurements. One of the core advantages of image compression is reduction of redundancy in the image data thus ensuring use of less space in data storage. Discrete wavelet transform is a very competent image compression scheme that results less computational complexity with no sacrifice in image quality. The proposed technique very efficiently compresses the images without deteriorating important details contained in the image where data comprises of multi resolution and multispectral imaging. The aim of this work is to develop an algorithm for image compression without compromising loss of important details contained in the image. An innovative wavelet synthesis approach is conceived based on wavelet scale correlation of the concordant detail bands such that the reconstructed image fabricates a compressed image. An entropy reduction criterion is used in parallel to PSNR for analytical analysis of the results. The subjective analysis supported by the objective analysis reveals that the results image compression through the proposed scheme is satisfactory in various noise environments. Discrete wavelet transform (DWT) using scale correlation is a compression approach that works effectively than the simple wavelet decomposition. Scale multiplication improves the localization accuracy significantly while keeping high detection efficiency.
