This paper proposes a new adaptive scheme for stereo image coding . The original left and right images are jointly coded in order to exploit the high correlation between the two images for a lossless coding. Our goal is to design an efficient transform that reduces the existing redundancy in the stereo pair. This approach is inspired by the lifting scheme (LS). First, illumination change compensation has been made. Secondly, the prediction filtering is locally adapted and is based on local horizontal and vertical gradient information. In the sense that small gradient evokes predictability in the same direction. The coefficients of the predictor are then optimized. Experimental results show improvement in term of performance and complexity compared to other proposed methods.

In this paper we address the problem of video segmentation. We propose a new method which combines an active contour and a watershed presegmentation. We first apply active contours to track moving objects with a basic motion criterion. Then, we eliminate the variation due to motion on the object boundaries by attracting the curve to the nearest boundaries of a watershed oversegmentation. We constrain the curve length to smooth the propagation driven by the distance to the watershed boundaries. The proposed method improves active contour segmentation and gives smoother results than watershed segmentation

This paper proposes a new method for the design of lifting filters to compute a multidimensional nonseparable wavelet transform. Our approach is stated in the general case, and is illustrated for the 2-D separable and for the quincunx images. Results are shown for the JPEG2000 database and for satellite images acquired on a quincunx sampling grid. The design of efficient quincunx filters is a difficult challenge which has already been addressed for specific cases. Our approach enables the design of less expensive filters adapted to the signal statistics to enhance the compression efficiency in a more general case. It is based on a two-step lifting scheme and joins the lifting theory with Wiener's optimization. The prediction step is designed in order to minimize the variance of the signal, and the update step is designed in order to minimize a reconstruction error. Application for lossy compression shows the performances of the method.

In this paper we address the problem of quincunx sampled images compression. Our objective is to define an efficient bit allocation method adapted to quincunx sampled images. We first estimate the subband optimal weightings for a global distortion estimation. These weightings are derived from the filters used to perform the quincunx wavelet transform. Then, we use our weightings in a model-based bit allocation procedure. Our method uses generalized Gaussians to approximate the probability density function of the wavelet coefficients in each subband. The bit allocation method which is proposed provides both low complexity and high performance.

This paper introduces the problem of designing a quincunx lifting scheme well-adapted to lossy compression applications. The main goal is to design quincunx filters adapted to the statistical properties of the input signal in order to perform a better signal reconstruction after deterioration due to a lossy coding. To perform such a filtering, the basic idea is to combine optimization methods and a lifting scheme. The latter is an attractive tool to perform wavelet transforms.

Quincunx sampling is of large interest for image coding applications. Recent remote sensors of satellites return quincunx sampled images. Moreover, a quincunx sampling allows the decomposition of the image into two channels and a twice as accurate multiresolution analysis as the dyadic one. This paper introduces a new construction of the quincunx wavelet transform. This new transform is a bidimensional extension of the factorization of a wavelet transform into a lifting scheme for finite and symmetrical low pass filters. The aim of this method is to deal with quincunx images with appropriate transforms while using advantages offered by the lifting scheme. This method allows us to find new efficient quincunx wavelet filters.