System and method for cross correlation with application to video motion vector estimator
February 10, 2015. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.Patent ReferencesHigh-speed correlating device Bidimensional correlation device Fingerprint verification method Device and method for optically correlating a pair of images Real-time programmable optical correlator Correlation operational apparatus for multi-dimensional images Process and device for the compression of image data by mathematical transformation effected at low cost, particularly for the transmission at a reduced rate of sequences of images Fingerprint verification method employing plural correlation judgement levels and sequential judgement stages Optical fingerprint correlator Fingerprint correlation system with parallel FIFO processor InventorsAssigneeApplicationNo. 388181 filed on 02/10/1995US Classes:382/236, Interframe coding (e.g., difference or motion detection)375/240.02, Adaptive375/240.16, Motion vector375/240.18, Transform375/240.22, Vector quantization375/240.24, Block coding382/248Transform codingExaminersPrimary: Greening, Wendy R.Attorney, Agent or FirmInternational ClassH04N 007/50AbstractMethod and apparatus for computing cross-correlations with application to image processing and video motion estimation, particularly in video compression applications, are described. Two-dimensional Fourier transform convolution techniques form a basis for novel techniques for performing two simultaneous two-dimensional cross correlations. The size of the input data blocks for the transformations are arbitrary. Apparatus for efficiently performing real-time cross correlations, including cross-correlations using Short Length Transforms (SLTs), using cascaded stages, multi-port memories, and multiple arithmetic units are also described. In video motion vector estimator application, data blocks within a current video frame are selected and converted to form a two-dimensional matrix of complex data. The complex matrix is transformed to the frequency domain to form the frequency domain representations of the selected data blocks. A set of search blocks within the previous video frame having a one-to-one correspondence with the selected data blocks, is then selected, converted into a complex data matrix, and transformed to the frequency domain to form the frequency domain representations of the selected search blocks. Once in the frequency domain, the sets of data corresponding to the data blocks and the search blocks are multiplied together and the product is inverse transformed to return to the spatial domain. The data then passes through an adjustment process to form the cross-correlations between the pairs of data blocks and search blocks.Other References
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