A Combined Fractal and Wavelet Angiography Image Compression Approach

A. Al-Fahoum, B. Harb
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引用次数: 17

Abstract

In this paper, a combined Fractal and Wavelet (CFW) compression algorithm targeting x-ray angiogram images is proposed. Initially, the image is decomposed using wavelet transform. The smoothness of the low frequency part of the image appears as an approximation image with higher self similarities, therefore, it is coded using a fractal coding technique. However, the rest of the image is coded using an adaptive wavelet thresholding technique. This model is implemented and its performance is compared with best performances of the available published algorithms. A data set containing 1000 x-ray angiograms is used to study the performance of the algorithm. A minimum compression ratio of 30 with a peak signal to noise ratio (PSNR) of 36 dB and percent diameter stenosis deviation of (<0.2%) was achieved. Results demonstrate the effectiveness of the proposed technique in obtaining a diagnostic quality of reconstructed images at very low bit rates.
一种分形和小波联合血管造影图像压缩方法
本文提出了一种针对x射线血管造影图像的分形和小波组合压缩算法。首先用小波变换对图像进行分解。图像低频部分的平滑度表现为具有较高自相似度的近似图像,因此采用分形编码技术对其进行编码。但是,图像的其余部分使用自适应小波阈值技术进行编码。实现了该模型,并将其性能与现有已发表算法的最佳性能进行了比较。用包含1000张x射线血管图像的数据集来研究该算法的性能。最小压缩比为30,峰值信噪比(PSNR)为36 dB,直径狭窄偏差百分比(<0.2%)。结果表明,所提出的技术在获得诊断质量的重建图像在非常低的比特率的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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