Abstract: There is provided a method for pre-processing a video stream for subsequent motion detection processing. The method comprises receiving a video stream of images, wherein each image in the video stream is represented by a first plurality of bits; enhancing the video stream of images by, for each image in the video stream: comparing the image to at least one previous image in the video stream so as to identify pixels where the image differs from the at least one previous image in the video stream, enhancing the image in those pixels where the image differs from the at least one previous image in the video stream; and converting the enhanced video stream of images so as to produce a converted video stream of images for subsequent motion detection processing, wherein each image in the converted video stream is represented by a second plurality of bits being lower than the first plurality of bits.

Abstract: Complex image data is transformed to a holographic representation of the image. A subset of the holographic representation is modeled. Model parameters constitute a compressed image representation. A two-dimensional Fourier transform can be applied to obtain the holographic image. Modeling includes applying an analysis portion of an adaptive analysis/synthesis linear prediction methodology to a subset of the holographic representation to obtain an autoregressive model. Prior to modeling, one-dimensional Fourier transform can be performed on the holographic representation and the linear prediction is one-dimensional. Model parameters are preferably quantized. Embodiments include determining error between the model and the model's input data. There the compressed image representation the error, which also can be quantized. The subset of the holographic representation can be less than all the representation. The subset can be a plurality of complete rows; preferably substantially symmetric about 0 Hz.