Image Coding Based on Contourlet Transformation | ||
| AL-Rafidain Journal of Computer Sciences and Mathematics | ||
| Article 12, Volume 15, Issue 2, December 2021, Pages 149-163 PDF (1.94 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.33899/csmj.2021.170018 | ||
| Authors | ||
| Sahlah Abd Ali Al-hamdanee1; Eman Abd Elaziz1; Khalil I. Alsaif2 | ||
| 1Department of Computer Science College of Computer Science and Mathematics University of Mosul, Mosul, Iraq | ||
| 2College of Computer Sciences and Mathematics University of Mosul | ||
| Abstract | ||
| The interest in coding was very high because it is widely relied on in the security of correspondence and in the security of information in addition to the need to rely on it in the storage of data because it leads to a pressure in the volume of information when storing it. In this research, image transformation was used to encode gray or color images by adopting parameters elected from contourlet transformations for image. The color images are acquired into the algorithm, to be converted into three slices (the main colors of the image), to be disassembled into their coefficients through contourlet transformations and then some high frequencies in addition to the low frequency are elected in order to reconstruct the image again. The election of low frequencies with a small portion of the high frequencies has led to bury some unnecessary information from the image components. The performance efficiency of the proposed method was measured by MSE and PSNR criteria to see the extent of the discrepancy between the original image and the recovered image when adopting different degrees of disassembly level, in addition, the extent to which the image type affects the performance efficiency of the approved method has been studied. When the practical application of the method show that the level of disassembly is directly proportional to the amount of the error square MSE and also has a great effect on the extent of correlation where the recovered image away from the original image in direct proportional with the increased degree of disassembly of the image. It also shows the extent to which it is affected by the image of different types and varieties, where was the highest value of the PSNR (58.0393) in the natural images and the less valuable in x-ray images (56.9295) as shown in table 4. | ||
| Keywords | ||
| Image Transformation; Contourlet Transformation; coding Techniques; color Digital image | ||
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