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 present a collection of methods and algorithms able to deal with high dynamic ranges of real pictures acquired by digital engines e.g., charge-coupled device (CCD/CMOS) cameras. An accurate image acquisition can be challenging under difficult light conditions. A few techniques that overcome dynamic range limitations problems are reported. The presented methods allow the recovery of the original radiance values of the final 8-bit-depth image starting from differently exposed pictures. This allows the capture of both low-and highlight details by merging the various pictures into a single map, thus providing a more faithful description of what the real world scene was. However, in order to be viewed on a common computer monitor, the map needs to be compressed and requantized while preserving the visibility of details. The main problem comes from the fact that the contrast of the radiance values is usually far greater than that of the display device. Various related techniques are reviewed and discussed.

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.

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.

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