Siemens Aktiengesellschaft

Andreas Weinlich

Andreas Hutter

Peter Amon

André Kaup

Johannes Rehm

For each array of pixels, an autoregressive pixel-prediction method is performed based on a weighted sum of reconstructed pixel values of reconstructed pixels in a specific neighborhood region adjacent to the current pixel to be coded. For determining the weights, the pixel values in a specific training region adjacent to the current pixel are taken into account. The coding method is characterized by an appropriate determination of the specific neighborhood region and the specific training region in case that reconstructed pixel values do not exist for all pixels in the neighborhood region and the training region. In such a case, the number of pixels in the neighborhood region is reduced to a number of reconstructed pixels until the ratio between the number of pixels in the training region and the number of pixels in the neighborhood region exceeds a predetermined threshold.

Autogressive pixel prediction in the neighborhood of image borders

The embodiments relate to pixel-prediction methods and devices that are based on one of a selection of one out of at least two model functions that provide a prediction function and an adaptive model function that is capable to predict intensity characteristics of reference pixels used for prediction.

Pixel-prediction for compression of visual data

A method codes a sequence of digital images, each image having the same image format and including a number of pixels with assigned pixel values. Motion parameters between first and second images are determined, where based on said motion parameters a motion compensation is performed for coding the sequence of images, where said motion parameters are included in the coded sequence of images. The motion parameters between a first image and a second image include a scalar field having scalar values for a plurality of image positions in the image format. The scalar field is determined such that gradient vectors derived from the scalar field correspond to motion vectors for the motion compensation.

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Windsbach, Germany

Andreas Weinlich