Implementation Of A Hybrid Color Image Compression Technique Using Principal Component Analysis And Discrete Tchebichef Transform (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
The proliferation of scientific and technological demands of high-resolution multimedia contenthas extremely increased the data volume in enterprise data centers and servers on the internet.The characterization of high-resolution picturescreates a great challenge to transfer files with the immensely colossal volume of image data over communication networks. The uploading/downloading time of large images has always been a keyproblemon the Internet. In addition to data communicationissues, high-resolution photo consumes larger storage capacity. Therefore, compression is an almost inevitable process towards the reduction of the transmission time and/or storage capacity requirements of images.Principle component analysis (PCA) and Discrete Tchebichef Transform (DTT) algorithmsare often employed for image compression in several references. In this paper, we propose a hybrid color image compression approachbased on PCA and DTT algorithms (PCADTT), which integrates the benefits of both PCA and DTT algorithms.Our hybrid approach exploits (i) PCA to reduce the dimensionality of the image; and (ii) DTT algorithm to enhance the image quality.The proposed technique has been assessed and related to a compression method that integrates DTT with a singular value decomposition (SVD) scheme (DTTSVD)using different performancemeasures including compression time (CT),compression ratio (CR), structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and universal quality index (UQI). The experimental results reveal that our proposed method outperformsthe existing method for all kinds of image content at a high compression ratio with lower computational complexity and retaining thequality of imagedata.