This paper presents a robust algorithm for video sequences stabilization. Motion estimation is achieved using block motion vectors. In this way the same motion estimator of mpeg encoder can be used. The simple use of block motion vectors can give unreliable global motion vectors and so elaborations are done to make the algorithm robust.

We describe an automatic image enhancement technique based on features extraction methods. The approach takes into account images in Bayer data format, captured using a CCD/CMOS sensor and/or 24-bit color images; after identifying the visually significant features, the algorithm adjusts the exposure level using a “camera response”-like function; then a final HUE reconstruction is achieved. This method is suitable for handset devices acquisition systems (e.g., mobile phones, PDA, etc.). The process is also suitable to solve some of the typical drawbacks due to several factors such as poor optics, absence of flashgun, and so forth.

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The proposed paper concerns the processing of images in digital format and, more specifically, particular techniques that can be advantageously used in digital still cameras for improving the quality of images acquired with a non-optimal exposure. The proposed approach analyses the CCDICMOS sensor Bayer data or the corresponding color generated image and, after identifying specific features, it adjusts the exposure level according to a 'camera response' like function.

This paper presents a novel technique to convert raster images in a Scalable Vector Graphic (SVG) format using Data Dependent Triangulation (DDT). The triangulation, a classical 3D graphic rendering approach, is here applied to digital images acquired by imaging consumer devices. Good quality rendering of real images has been obtained making use of some ad-hoc heuristics able to properly manage advanced SVG features (e.g. path, gradient, filter effects). Experiments and comparisons with existing techniques confirm the effectiveness of the proposed strategy.