The frequency domain plays an important role in image processing to smooth, enhance, and detect edges of images. Although image data typically does not include imaginary values, the fast Fourier transform (FFT) has been used for obtaining spect

基于改进K-means的压缩IP 由于k-means本身受异常点影响较大，这里采用迭代k-means的方法，降低异常点的影响，减少计算量和提高聚类数目的灵活性。并添加合并异常聚类方法，提高聚类的均匀性-K-means based on improved compression IP As k-means itself is influenced by outliers, where an iterative k-means method to reduce the impact of o