PERFORMANCE COMPARISON OF RUN-LENGTH, HUFFMAN AND LEMPLE-ZIV ALGORITHMS ON GRAY-SCALE PNG AND JPG IMAGES COMPRESSION
Abstract
Image compression plays a crucial role in optimising storage and transmission efficiency. This paper evaluates the performance of Run-Length Encoding (RLE), Huffman Coding, and Lempel-Ziv-Welch (LZW) algorithms for compressing grayscale PNG and JPG images. The study analyses their effectiveness using compression ratio, bits per pixel, and compression time as key performance metrics. Results indicate that LZW achieved the highest compression ratio, ranging from 1.0113 to 2.4020, making it the most efficient for file size reduction. RLE performed moderately, with compression ratios between 0.5456 and 2.3895, while Huffman Coding exhibited the lowest ratios, ranging from 0.2646 to 1.0680. In terms of bits per pixel, LZW recorded the lowest values, highlighting its ability to reduce data while preserving image quality. Compression time analysis revealed that RLE was the fastest, with processing times between 0.0019 and 0.0468 seconds, making it suitable for real-time applications. LZW and Huffman Coding demonstrated a trade-off between compression efficiency and speed. These findings establish LZW as the most effective algorithm for high compression with minimal quality loss, while RLE remains the best option for speed-critical applications.
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