CAJ | 학술논문

医学超声图像存在特有的斑点噪声,大大降低了图像质量,必须进行降噪处理.多小波具有比单小波分解更加精确、去噪效果更好的特点.对超声图像进行分形插值多小波分解,根据多小波分解后的能量分布特性,提出了改进多层阅值与模糊聚类相结合方法,将小波系数模糊聚类分成噪声和信号两类.然后在不同尺度对信号小波系数进行不同阈值萎缩处理,实现降噪目的.结果表明该方法优于硬阈值和软阈值法,可有效地降低图像斑点噪声并保留图像细节.
의학초성도상존재특유적반점조성,대대강저료도상질량,필수진행강조처리.다소파구유비단소파분해경가정학、거조효과경호적특점.대초성도상진행분형삽치다소파분해,근거다소파분해후적능량분포특성,제출료개진다층열치여모호취류상결합방법,장소파계수모호취류분성조성화신호량류.연후재불동척도대신호소파계수진행불동역치위축처리,실현강조목적.결과표명해방법우우경역치화연역치법,가유효지강저도상반점조성병보류도상세절.
There are inherent speckle noises in the medical ultrasound image.Image denoising is necessary for lower image quality.Multiwavelet has higher resolution and better denoising effect than scalar wavelet.Therefore,the modified multilevel threshold with fuzzy clustering is proposed based on the energy distribution of multiwavelet coefficients.First the ultrasound image is discomposed to multiwavelet domain.Then its coefficients are separated into noise and signal classes with fuzzy clustering.The signal coefficients are shrunk with different thresholds for image de-noising on the different scales.The result indicates the method is more effective than hard threshold and soft threshold.The speckle noise in the original image is removed efficiently and at the same time the image details are reserved.