Efficient Implementation of Searchless Fractal Image Compression on Low-cost FPGA for Real-Time Encoding

Self-similarity within images is utilized by Fractal Image Compression (FIC) method to provide potential benefit of high compression ratio, good recovery performance, flexible recovery resolution, and fast decoding process.Nevertheless, FIC has a significant drawback-its encoding process is highly time-consuming, particularly when a fullsearch approach is employed.To address this issue, searchless-based approaches have been developed and implemented in hardware to enable real-time encoding.Despite their advantages, existing hardware designs often require significant hardware resources, making them unsuitable for low-cost FPGA platforms.In this paper, a real-time and hardware-effecient architecture is proposed for encoding images with searchless-based FIC method, optimized for low resource utilization.The proposed design encoded the image blocks in different sizes based on quadtree approach.The design was synthesized and implemented on a low-cost FPGA, with circuit-level optimizations using parallelism and pipelining to enable real-time image encoding.Its performance was quantitatively assessed based on encoding time, hardware resource utilization, peak signal-to-noise ratio (PSNR), and compression ratio.With an operating frequency of 50 MHz, a run time of 9.65 ms can be achieved for an 5125128 image, which is equivalent to 103 images which can be encoded per second.The design consumes less than half of the total device resource in the low-cost Cyclone V SoC FPGA.The average PSNR and compression ratio achieved are 32 dB and 14:1 respectively.

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Publication Details

Journal
Journal of Soft Computing and Data Mining
Published
2025-06-30
DOI
https://doi.org/10.30880/jscdm.2025.06.01.010
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
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article

Efficient Implementation of Searchless Fractal Image Compression on Low-cost FPGA for Real-Time Encoding

Waheed Ali H. M. Ghanem, Abdullah B. Nasser, Antar Shaddad H. Abdul-Qawy, Abdul‐Malik H. Y. Saad et al.
Journal of Soft Computing and Data Mining
Chaos-based Image/Signal Encryption
article

Efficient Implementation of Searchless Fractal Image Compression on Low-cost FPGA for Real-Time Encoding

Waheed Ali H. M. Ghanem, Abdullah B. Nasser, Antar Shaddad H. Abdul-Qawy, Abdul‐Malik H. Y. Saad, Mohammed S. Mohammed, Hisham Haider Yusef Sa'ad, Nayef Abdulwahab Mohammed Alduais, Zhia Hao Chai
article en

Abstract

Self-similarity within images is utilized by Fractal Image Compression (FIC) method to provide potential benefit of high compression ratio, good recovery performance, flexible recovery resolution, and fast decoding process.Nevertheless, FIC has a significant drawback-its encoding process is highly time-consuming, particularly when a fullsearch approach is employed.To address this issue, searchless-based approaches have been developed and implemented in hardware to enable real-time encoding.Despite their advantages, existing hardware designs often require significant hardware resources, making them unsuitable for low-cost FPGA platforms.In this paper, a real-time and hardware-effecient architecture is proposed for encoding images with searchless-based FIC method, optimized for low resource utilization.The proposed design encoded the image blocks in different sizes based on quadtree approach.The design was synthesized and implemented on a low-cost FPGA, with circuit-level optimizations using parallelism and pipelining to enable real-time image encoding.Its performance was quantitatively assessed based on encoding time, hardware resource utilization, peak signal-to-noise ratio (PSNR), and compression ratio.With an operating frequency of 50 MHz, a run time of 9.65 ms can be achieved for an 5125128 image, which is equivalent to 103 images which can be encoded per second.The design consumes less than half of the total device resource in the low-cost Cyclone V SoC FPGA.The average PSNR and compression ratio achieved are 32 dB and 14:1 respectively.

Journal of Soft Computing and Data MiningVol. 6(1)
Openalex Percentile: Top 77%
Chaos-based Image/Signal Encryption
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