Paulo Nunes

ISCTE - University Institute of Lisbon (ISCTE-IUL), Information Science and Technology, Faculty Member

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Papers by Paulo Nunes

Image analysis towards very low bitrate video coding

by Manuel Menezes de Sequeira and Paulo Nunes

Very low bitrate video coding became in the last years one of the most important areas of image c... more Very low bitrate video coding became in the last years one of the most important areas of image communication due to the identiﬁcation of several very low bitrate applications such as mobile videotelephony, multimedia mail, electronic newspapers, entertainment, traﬃc control, and interactive data bases.

Since conventional video coding techniques are reaching a saturation point, a new generation of techniques, aiming at a deeper “understanding” of the image, is being studied. In this context, image analysis, particularly the identiﬁcation of regions or objects in images (segmentation), is an important step in very low bitrate video coding, since it will lead to a better representation of images and consequently to an improvement of the encoded image quality (for a ﬁxed bitrate).

This paper describes a segmentation algorithm based on split & merge and shortest spanning trees (SST). The image is ﬁrst split according to a quad tree structure and then the resulting regions are merged, using the SST concept, in three steps: merge, elimination of small regions and control of the number of regions.

Results are presented for video sequences from studio and mobile videotelephony, which show the good properties of the algorithm for application in very low bitrate video coding schemes.

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Image segmentation towards new image representation methods

by Manuel Menezes de Sequeira, Paulo Nunes, and Paulo Nunes

Very low bit-rate video coding has recently become one of the most important areas of image commu... more Very low bit-rate video coding has recently become one of the most important areas of image communication and a large variety of applications have already been identified. Since conventional approaches are reaching a saturation point, in terms of coding efficiency, a new generation of video coding techniques, aiming at a deeper “understanding” of the image, is being studied. In this context, image analysis, particularly the identification of objects or regions in images (segmentation), is a very important step. This paper describes a segmentation algorithm based on split and merge. Images are first simplified using mathematical morphology operators, which eliminate perceptually less relevant details. The simplified image is then split according to a quad tree structure and the resulting regions are finally merged in three steps: merge, elimination of small regions and control of the number of regions.