Abstract
The development of multimedia and digital imaging has led to high quantity of data required to represent modern imagery. This requires large disk space for storage, and long time for transmission over computer networks, and these two are relatively expensive. These factors prove the need for images compression. Image compression addresses the problem of reducing the amount of space required to represent a digital image yielding a compact representation of an image, and thereby reducing the image storage/transmission time requirements. The key idea here is to remove redundancy of data presented within an image to reduce its size without affecting the essential information of it. We are concerned with lossless image compression in this paper. Our proposed approach is a mix of a number of already existing techniques. Our approach works as follows: first, we apply the well-known Lempel-Ziv-Welch (LZW) algorithm on the image in hand. What comes out of the first step is forward to the second step where the Bose, Chaudhuri and Hocquenghem (BCH) error correction and detected algorithm is used. To improve the compression ratio, the proposed approach applies the BCH algorithms repeatedly until “inflation” is detected. The experimental results show that the proposed algorithm could achieve an excellent compression ratio without losing data when compared to the standard compression algorithms.
Highlights
Image applications are widely used, driven by recent advances in the technology and breakthroughs in the price and performance of the hardware and the firmware
The results show that the proposed method has higher compression ratio than the standard compression algorithm mentioned above
In order to demonstrate the compression performance of the proposed method, we compared it with some representative lossless image compression techniques on the set of ISO test images that were made available to the proposer that were shown in the first column in all tables
Summary
Prince Abdulah Bin Gazi Faculty of Information Technology, Al-Balqa Applied University, Salt, Jordan; 2The Computer Information Systems Department, College of Information Technology, Al-Hussein Bin Talal University, Ma’an, Jordan
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