Many computational vision routines can be regarded as recognition and retrieval of echoes in space or time. Cepstral analysis is a powerful nonlinear adaptive signal processing methodology widely used in many areas such as: echo retrieval and removal, speech processing and phoneme chunking, radar and sonar processing, seismology, medicine, image deblurring and restoration, and signal recovery. The aim of this paper is: (1) To provide a brief mathematical and historical review of cepstral techniques. (2) To introduce computational and performance improvements to power and differential cepstrum for use in detection of echoes; and to provide a comparison between these methods and the traditional cepstral techniques. (3) To apply cepstrum to visual tasks such as motion analysis and trinocular vision. And (4) to draw a brief comparison between cepstrum and other matching techniques. The computational and performance improvements introduced in this paper can e applied in other areas that frequently utilize cepstrum.