Search

In this paper, we propose a fast disparity and motion estimation for multi-view video coding (MVC). When implementing MVC, one of the most critical problems is heavy computational complexity caused by the large amount of information in multi-view sequences. Hence, a fast algorithm is essential. To reduce this computational complexity, we adaptively controlled a search range considering the reliability of each macroblock. In order to estimate this reliability, we calculated the difference between the predicted vectors that were obtained from different methods. When working with conventional encoders, vectors can be predicted using median filtering from causal blocks. Moreover, we calculated another predicted vector using multi-view camera geometry or the relationship between the disparity and motion vectors. We assumed that this difference indicated the reliability of the current macroblock. By using these properties, we were able to determine new search range and reduce the number of searching points within the limited window. The proposed MVC system was tested with several multiview sequences to evaluate performance. Experimental results showed that the proposed algorithm was able to reduce processing time by maximumly 70-80% in estimation process. Index Terms--Joint disparity/motion estimation, fast motion estimation, Multi-view Video Coding

This paper presents an efficient joint disparity-motion estimation algorithm and a fast motion estimation algorithm in an MPEG-4 compatible stereoscopic sequence codec for 3D broadcasting. In stereoscopic sequence coding, the critical problems to be solved are double bandwidth and computational complexity. However, the previous trials to reduce coding bits have increased computational complexity. In this paper, we try to implement fast algorithms for stereoscopic sequences while maintaining high coding efficiency. Joint disparity-motion estimation can increase coding efficiency and reduce the computational complexity of the stereoscopic codec by using the relationship between the disparity and motion fields. The disparity vectors are estimated by using the left and right motion vectors and the previous disparity vectors in each time frame. In order to obtain more accurate disparity vectors, we employ the spatial prediction process, after joint estimation. From joint estimation and spatial prediction, we can obtain the accurately predicted disparity vectors and then increase the coding efficiency from those predicted vectors. Moreover, we propose a fast motion estimation algorithm which utilizes correlation between the motion vectors of the neighboring blocks. We confirmed that the PSNR of the proposed method is 1.0-2.0dB higher than ones of conventional methods. In addition, the processing time is reduced by almost 1/10. Index Terms--Joint disparity-motion estimation, fast motion estimation, stereo sequences

This paper presents advanced rate control technologies for 3D-HDTV. We remodel the quadratic rate-distortion model for 3D multiview sequences based on their picture types. The proposed method consists of two levels for more accurate bits rate control. In a frame level, it sets quantization parameters based on HVS (Human Visual System) and reduces error bits by remodeling rate-quantization. In a MB level, rate control is activated to provide stricter buffer regulations and higher bit rate encoding based on the target bits and the quantization parameters calculated at the frame level. The proposed algorithm shows improvements in rate control as well as in PSNR compared to the conventional methods. It also provides more accurate rate control and higher image quality than TM5 and TMN8 at various bits rates. Index Terms--Rate control, Quality control, Multiview sequence.

In this paper, we propose a new deinterlacing algorithm, which uses directional interpolation and motion compensation. In the proposed method, intrafield interpolation is first performed in the direction that shows the highest correlation. Second, motion estimation is performed between two fields of the same parity. The motion vector is further refined in half-pixel accuracy. In the conventional motion compensated methods, a prefilter such as line averaging, is applied to interpolate missing lines prior to motion estimation between opposite parity fields. The proposed method does not require this prefilter since block matching is performed between the same parity fields. Finally, we apply a test and use either directional interpolation or motion compensated interpolation depending on the test result. Experimental results demonstrate that the proposed method provides better performances than conventional deinterlacing algorithms. Index Terms--deinterlacing, directional interpolation, interlaced scan, motion compensation.

In this paper, we present a color interpolation technique based on artificial neural networks for a single-chip CCD (charge-coupled device) camera with a Bayer color filter array (CFA). Single-chip digital cameras use a color filter array and an interpolation method in order to produce high quality color images from sparsely sampled images. We have applied 3-layer feedforward neural networks in order to interpolate a missing pixel from surrounding pixels. And we compare the proposed method with conventional interpolation methods such as the bilinear interpolation method and cubic spline interpolation method. Experiments show that the proposed interpolation algorithm based on neural networks provides a better performance than the conventional interpolation algorithms.