JOURNAL ARTICLE

Improved Image Compression Scheme Using Hybrid Encoding Algorithm

Yusra Ahmed SalihAree Ali MohammedLoay E. George

Year: 2019 Journal:   Kurdistan Journal of Applied Research Vol: 4 (2)Pages: 90-101   Publisher: Slemani Polytechnic University

Abstract

A color image compression is the most challenging task in the field of multimedia. During last decades several techniques are developed for improving the quality, coding time and compression ratio using different coding strategies. In this work, an effective compression method for hybrid images is proposed based on the discrete wavelet transformation and hybrid encoding algorithm (Huffman and SPIHT). This paper's primary participation is to take advantage of the hybrid encoding technique to maintain the quality of the reconstructed image and the reduction of time complexity. The sample test images are taken from both standard image database and high-quality images (SD and HD). The performance of the proposed scheme is evaluated by using different metrics such as (PSNR, compression ratio and encoding time). Test results indicate that the time and compression ratio of encoding are improved in the expense of the image quality.

Keywords:
Huffman coding Image compression Lossless compression Computer science Artificial intelligence Compression ratio Data compression Texture compression Data compression ratio Set partitioning in hierarchical trees Computer vision Encoding (memory) Context-adaptive binary arithmetic coding Algorithm Image quality Standard test image Coding (social sciences) Pattern recognition (psychology) Image (mathematics) Mathematics Image processing

Metrics

6
Cited By
0.43
FWCI (Field Weighted Citation Impact)
21
Refs
0.66
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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