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Study On Optimization Method Of Quantization Step And The Image Quality Evaluation For Medical Ultrasonic Echo Image Compression By Wavelet Transform

机译:小波变换的医学超声回波图像压缩量化步长优化方法及图像质量评估研究

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摘要

In this paper, we attemped optimized quantization method in JPEG2000 application for medical ultrasonic echo images. JPEG2000 has been issued as the new standard for image compression technique, which is based on Wavelet Transform (WT). There are two quantization methods in JPEG2000. One is the scalar derived quantization (SDQ), which is usually used in standard JPEG2000, and the other is the scalar expounded quantization (SEQ). the latter can be optimized by user. Therefore, this paper is to find an optimization method of quantization step, which is determined by Genetic Algorithm (GA). Then, the results are compared with standard JPEG2000 (SDQ) and arithmetic average method, the proposes improve image quality and compression rate for medical ultrasonic images. The image quality is evaluated by objective assessment, PSNR (Peak Signal to noise Ratio) and subjective assessment is evaluated by ultrasonographers form Tokai University Hospital and Tokai University Hachioji Hospital. The results show that SEQ determined by Genetic Algorithm provides better image quality than SDQ and SEQ determined by arithmeti'c average method.
机译:在本文中,我们尝试了在JPEG2000中用于医学超声回波图像的优化量化方法。 JPEG2000已发布为基于小波变换(WT)的图像压缩技术的新标准。 JPEG2000中有两种量化方法。一个是标量派生量化(SDQ),通常在标准JPEG2000中使用,另一个是标量扩展量化(SEQ)。后者可以由用户优化。因此,本文旨在寻找一种由遗传算法(GA)确定的量化步长的优化方法。然后,将结果与标准JPEG2000(SDQ)和算术平均方法进行比较,提出了改进医学超声图像的图像质量和压缩率的方法。通过客观评估,PSNR(峰值信噪比)评估图像质量,并由东海大学医院和东海大学八王子医院的超声医师评估主观评估。结果表明,遗传算法确定的SEQ的图像质量优于SDQ和算术平均法确定的SEQ。

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