针对医学CT图像边缘模糊、对比度低、噪声污染严重等特点，本文提出了短时分数阶傅里叶变换域的向量无穷范数方法，用于CT 图像的边缘检测。短时分数阶傅里叶变换域的虚部能够反映非平稳信号的局部信息。首先，对一维非平稳信号做短时分数阶傅里叶变换，得到短时分数阶傅里叶变换域；其次，计算变换域虚部的向量无穷范数，将二维时频面映射为一维信号，得到非平稳信号的边缘信息。实验表明本文方法具有检测信号边缘的能力，能够有效提取CT 图像的边缘，对弱边缘信号也具有较好的检测结果。与经典微分算子和小波变换比较表明，本文方法对CT 图像边缘检测表现优良，对噪声污染图像具有较好的鲁棒性。

As medical CT images always have blurred edges, low contrast, and noise pollution, etc., a new method based on Short-time Fractional Fourier Transform (STFrFT) and infinite-norm is proposed to detect edges of CT images. The imaginary part of STFrFT domain represents the local feature of non-stationary signal. At first, transform the non-stationary signal to STFrFT domain by short-time fractional Fourier transform. Then, obtain the vector infinite norm of STFrFT domain. Two dimensional time-frequency plane is mapped to a one-dimensional signal which shows the edges of the non-stationary signal. Experiment results demonstrate that the proposed method reveals a remarkable performance in detecting the edges of CT images, as well as weak edges. Compared with the results of differential operators and wavelet transform, the proposed approach performs better in the edge detection of CT images and is robust with noise.