应用小波变换检测细胞显微荧光图像中的囊泡

文章提出了一种用小波变换来检测生物荧光图像中囊泡的方法。作者用à trous小波对图像进行小波变换，然后求出每层系数的中值绝对偏差σ，并用t=kσ/0.67作为阈值对每层系数进行门限滤波，然后通过提取小波变换系数来重构图像。通过设计实验与常用的“rolling ball”算法对比，发现小波变换算法在低信噪比的情况下，具有更好的灵敏度；对于形状大小不同的信号，具有更好的稳定性；而且对于信号的细节信息具有更好的保真性。

Application of Wavelet Transform in Vesicle Detection from Biological Fluorescence Images

This paper present a wavelet transform method to detect vesicles in fluorescence images from biological experiments. It based on à trous wavelet transform to detect vesicles in fluorescence images. To get different wavelet planes, three levels wavelet transform using original image was made, and then median absolute deviation estimate σ was calculated for each wavelet plane. With this σ, a hard threshold method (t=kσ/0.67) was applied to filter out the noise coefficients of each wavelet plane, which allowed to enhance multiscale peaks due to spots. Vesicles were detected via setting a threshold in reconstructed image combining information from different levels of wavelet planes. Meanwhile, the authors compared the "rolling ball" algorithm with the wavelet transform algorithm in their effectiveness of vesicle detection, and found that wavelet transform algorithm is more sensitive in low signal to noise ratio images, more stable for different sizes signal, and better fidelity about the details of signal.