Abstract In ultrasonic testing, the accuracy of flaw sizing is normally low because of the use of relatively long wavelengths. In this paper, we investigate two signal processing methods: block filtering and block filtering with deconvolution for the improvement of lateral resolution and flaw sizing accuracy in ultrasonic testing. In block filtering, each returned echo is Fourier transformed, and a band of frequency components is used to build a C-scan image that is based on the estimation of flaw size. In deconvolution, a block-filtered C-scan image is deconvolved with the point spread function of a transducer by a frequency-domain Weiner deconvolution algorithm. The deconvolved C-scan image is then used for the determination of flaw size. A unique feature in our implementation of the deconvolution technique is that the point spread function is obtained based on an ultrasonic scattering model1. By doing so, a separate experiment needed for measuring the point spread function is avoided2. Experiments were conducted on several artificial flaws with different sizes (flat-bottom holes). It was found that the C-scan images, after processing, become sharper; flaw sizing errors were reduced after block filtering and could be further reduced by deconvolution if proper parameters in the deconvolution were selected.