We suggest a method for sharpening an image or video stream without using convolution, as in unsharp masking, or deconvolution, as in constrained least-squares filtering. Instead, our technique is based on a local analysis of phase congruency and hence focuses on perceptually important details. The image is partitioned into overlapping tiles, and is processed tile by tile. We perform a Fourier transform for each of the tiles, and define congruency for each of the components in such a way that it is large when the component's neighbours are aligned with it, and small otherwise. We then amplify weak components with high phase congruency and reduce strong components with low phase congruency. Following this method, we avoid strengthening the Fourier components corresponding to sharp edges, while amplifying those details that underwent a slight or moderate defocus blur. The tiles are then seamlessly stitched. As a result, the image sharpness is improved wherever perceptually important details are present.