In this paper a new image compression schema that uses three-dimensional discrete cosine transform and relies on twodimensional discrete wavelet transform, for image classification, is proposed. The proposed technique utilizes a modified quantization table and a method for converting a three-dimensional image cube into a one-dimensional array, which provides better coding efficiency in the run length coding step. To ensure faster performance, this technique provides proposed parallel computation system. Several images have been used to test the proposed algorithm. Experimental results demonstrate that the proposed algorithm outperforms previous compression methods in terms of peak-signal-to-noise ratio with a lower compression bit rate.
Emara, M., Abdel-Kader, R., & Yasein, M. (2017). Image Compression Using Advanced Optimization Algorithms. Port-Said Engineering Research Journal, 21(1), 95-108. doi: 10.21608/pserj.2017.33445
MLA
Mohamed E. Emara; Rehab F. Abdel-Kader; Mohamed S. Yasein. "Image Compression Using Advanced Optimization Algorithms", Port-Said Engineering Research Journal, 21, 1, 2017, 95-108. doi: 10.21608/pserj.2017.33445
HARVARD
Emara, M., Abdel-Kader, R., Yasein, M. (2017). 'Image Compression Using Advanced Optimization Algorithms', Port-Said Engineering Research Journal, 21(1), pp. 95-108. doi: 10.21608/pserj.2017.33445
VANCOUVER
Emara, M., Abdel-Kader, R., Yasein, M. Image Compression Using Advanced Optimization Algorithms. Port-Said Engineering Research Journal, 2017; 21(1): 95-108. doi: 10.21608/pserj.2017.33445