一种改进的指纹图像小波系数演化技术

K. T. Shanavaz, P. Mythili
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引用次数: 8

摘要

本文提出了一种改进的小波系数演化技术,用于指纹图像的压缩和重建。FBI指纹压缩标准[1,2]使用了cdf 9/7小波滤波系数。提升格式是用较少的滤波系数表示经典小波的有效方法[3,4]。本文采用遗传算法(GA)对cdf 9/7小波演化出更好的提升滤波系数,对指纹图像进行压缩重构,得到更好的图像质量。由于提升滤波系数与相应的经典小波滤波系数相比数量较少,因此使用遗传算法可以以更快的速度进化。当压缩比为16∶1时,采用最佳提升滤波系数,重构图像的峰值信噪比(PSNR)较好。这些演化系数也适用于其他压缩比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved technique for evolving wavelet coefficients for fingerprint image compression
In this paper, an improved technique for evolving wavelet coefficients refined for compression and reconstruction of fingerprint images is presented. The FBI fingerprint compression standard [1, 2] uses the cdf 9/7 wavelet filter coefficients. Lifting scheme is an efficient way to represent classical wavelets with fewer filter coefficients [3, 4]. Here Genetic algorithm (GA) is used to evolve better lifting filter coefficients for cdf 9/7 wavelet to compress and reconstruct fingerprint images with better quality. Since the lifting filter coefficients are few in numbers compared to the corresponding classical wavelet filter coefficients, they are evolved at a faster rate using GA. A better reconstructed image quality in terms of Peak-Signal-to-Noise-Ratio (PSNR) is achieved with the best lifting filter coefficients evolved for a compression ratio 16∶1. These evolved coefficients perform well for other compression ratios also.
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