Wavelet Transform Domain for Deep Image Compression Using High Frequency Sub-Band Prediction
Main Article Content
Abstract
This procedure demonstrates a Two Dimensional Discrete Cosine Transform (2D-DCT) system with quantization and zigzag layout. The JPEG picture compression approach uses this process as the foundation and main channel. Utilizing the 2D- DCT property, the calculation divides the overall process into compression and decompression. Even though the data in the images remained the same, the pixel was reduced predicated on the quantization and zigzag process. Division operation is used throughout the quantization process. As a result, this procedure minimizes data loss during decompression. The theoretical research offered in this study offers some fresh perspectives on how local variation behaves when JPEG compression is applied. Additionally, it might be utilised in a few aspects of image processing and analysis, including picture enhancement, image quality evaluation, and image filtering. MATLAB is used for this project, and improved vector quantization is used. Using the compression ratio, MSE, and PSNR, we can produce compressed pictures.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
