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Color Image Compression System by using Block Categorization Based on Spatial Details and DCT Followed by Improved Entropy Encoder
- Source :
- Iraqi Journal of Science. :3127-3140
- Publication Year :
- 2020
- Publisher :
- University of Baghdad College of Science, 2020.
-
Abstract
- In this paper, a new high-performance lossy compression technique based on DCT is proposed. The image is partitioned into blocks of a size of NxN (where N is multiple of 2), each block is categorized whether it is high frequency (uncorrelated block) or low frequency (correlated block) according to its spatial details, this done by calculating the energy of block by taking the absolute sum of differential pulse code modulation (DPCM) differences between pixels to determine the level of correlation by using a specified threshold value. The image blocks will be scanned and converted into 1D vectors using horizontal scan order. Then, 1D-DCT is applied for each vector to produce transform coefficients. The transformed coefficients will be quantized with different quantization values according to the energy of the block. Finally, an enhanced entropy encoder technique is applied to store the quantized coefficients. To test the level of compression, the quantitative measures of the peak signal-to-noise ratio (PSNR) and compression ratio (CR) is used to ensure the effectiveness of the suggested system. The PSNR values of the reconstructed images are taken between the intermediate range from 28dB to 40dB, the best attained compression gain on standard Lena image has been increased to be around (96.60 %). Also, the results were compared to those of the standard JPEG system utilized in the “ACDSee Ultimate 2020†software to evaluate the performance of the proposed system.
- Subjects :
- General Computer Science
020206 networking & telecommunications
02 engineering and technology
General Chemistry
computer.file_format
Lossy compression
JPEG
General Biochemistry, Genetics and Molecular Biology
Compression ratio
0202 electrical engineering, electronic engineering, information engineering
Discrete cosine transform
020201 artificial intelligence & image processing
Entropy encoding
Pulse-code modulation
computer
Encoder
Algorithm
Image compression
Mathematics
Subjects
Details
- ISSN :
- 23121637 and 00672904
- Database :
- OpenAIRE
- Journal :
- Iraqi Journal of Science
- Accession number :
- edsair.doi...........5a03f40ff1d2d39ac223c3f2855c6558