Abstract
Multi-view registration is an essential step in order to generate the side information for multi-view Distributed Video Coding. As stated in our previous work (Ciobanu and Crte-Real, Multimed Tools Appl 48(3):411-436, 2010) it can be achieved by SIFT (scale-invariant feature transform) generated keypoint matches. The registration accuracy is vital for the adequate generation of side information and it directly depends on the reliable match of possibly all the available point to point correlations between two complete-overlapped views. We propose a solution to this problem based on iterative filtering of SIFT-generated keypoint matches, using the Hough transform and block matching. It aims the generic, real-life and constraint-free scenarios having an arbitrarily close angle between the two views. Practical results show an overall significant reduction of the outliers while maintaining a high rate of correct matches.

Abstract
Inter-camera registration in multi-view systems with overlapped views has a particularly long and sophisticated research history within the computer vision community. Moreover, when applied to Distributed Video Coding, in systems with at least one moving camera it represents a real challenge due to the necessary data at decoder for generating the side information without any a priori knowledge of each instant camera position. This paper proposes a solution to this problem based on successive multi-view registration and motion compensated extrapolation for on-the-fly re-correlation of two views at decoder. This novel technique for side information generation is codec-independent, robust and flexible with regard to any free motion of the cameras. Furthermore, it doesn't require any additional information from encoders nor communication between cameras or offline training stage. We also propose a metric for an objective assessment of the multi-view correlation performance.

Abstract
In this paper we provide an analysis of rate-distortion (R-D) relationship in an H.264 codec using as quality metric Structural Similarly Information (SSIM). This study focus on the quantization parameter, namely rate-quantization (R-Q) functions and distortion-quantization (D-Q) functions. Together, these functions allow a better understanding of the rate-distortion (R-D) behaviour of an H.264 video codec, which is the key issue of optimum bit allocation. Initial results are presented and discussed.

Abstract
This paper presents a joint coding scheme for multiple H.264/AVC video programs. Channel bandwidth is divided among different programs according its complexity. Several complexity metrics are assessed. Initial results are presented and discussed.

Abstract
In this piper, we propose a method to broadcast digital video programs in which the channel capacity is dynamically distributed among video programs according to each video program particular complexity. A bit rate control algorithm based on the Structural Similarity Index as the measure of video program complexity is examined. Initial results show that a uniform picture quality among video programs can be obtained.

Abstract
The geometric correction of images under the scope of remote sensing applications is still mostly a manual work. This is a time and effort consuming task associated with an intra-and inter-operator subjectivity. One of the main reasons may be the lack of a proper evaluation of the different available automatic image registration ( AIR) methods, since some of them are only adequate for certain types of applications/data. In order to fulfill a gap in this context, a first reference dataset of pairs of images comprising some types of geometric distortions was created, different spatial and spectral resolutions, and divided according to the Level 1 of CORINE Land Cover nomenclature ( European Environment Agency). This dataset will allow for gaining perception of the abilities and limitations of some AIR methods. Some AIR methods were evaluated in this work, including the traditional correlation-based method and the SIFT approach, for which a set of measures for an objective evaluation of the geometric correction process quality was computed for every combination of pair of images/AIR method. The reference dataset is available from an internet address, being expected that it becomes a channel of interaction among the remote sensing community interested in this field.