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.

Date Published: 21 May 1993
PDF: 12 pages
Proc. SPIE 1902, Nonlinear Image Processing IV, (21 May 1993); doi: 10.1117/12.144761

Published in SPIE Proceedings Vol. 1902:
Nonlinear Image Processing IV
Edward R. Dougherty; Jaakko T. Astola; Harold G. Longbotham, Editor(s)