Head-related Transfer Functions (HRTFs) refer to the spectral filtering from sound sources to listeners' eardrums or ear canals. As an effective model structure, the degree of the IIR filter approximation of the H...
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This paper introduces a new kind of recovery method which is the combination of Bayesian estimation and wavelet threshold. Wavelet coefficients of signals show strong characteristics of the non-Gauss statistics, its p...
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This paper mainly presents two approaches for image retrieval. There is some faintness in color locating in quantification boundary when image color is quantized. The membership function in fuzzy set theory can descri...
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SIFT (Scale Invariant Feature Transform) is used to solve visual tracking problem, where the appearances of the tracked object and scene background change during tracking. The implementation of this algorithm has five...
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A new algorithm of color image blind watermarking based on BP neural network and wavelet significant tree is proposed. In YCbCr, the luminance component is decomposed with wavelet, and the wavelet significant tree can...
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An efficient rate control scheme for H.264 encoding has been proposed, where p domain source modeling, which was first used in block-based DCT coding system such as H.263, MPEG-2 and MPEG-4, is introduced. For accurat...
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An efficient rate control scheme for H.264 encoding has been proposed, where p domain source modeling, which was first used in block-based DCT coding system such as H.263, MPEG-2 and MPEG-4, is introduced. For accurate rate control, parameter thetas, the slope of the linear function of bit rate R vs. p, should be estimated in advance for each frame. Least-Mean-Square (LMS) algorithm is adopted for the estimation of thetas, which is further refined by a new factor thetas-ratio for each frame. Simulation results for standard test sequences show that, compared with JVT-H017, the new algorithm achieves better coding performance, while the output bit rates are more accurate.
This letter proposes a novel method of compressed video super-resolution reconstruction based on MAP-POCS (Maximum Posterior Probability-Projection Onto Convex Set). At first assuming the high-resolution model subject...
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This letter proposes a novel method of compressed video super-resolution reconstruction based on MAP-POCS (Maximum Posterior Probability-Projection Onto Convex Set). At first assuming the high-resolution model subject to Poisson-Markov distribution, then constructing the projecting convex based on MAP. According to the characteristics of compressed video, two different convexes are constructed based on integrating the inter-frame and intra-frame information in the wavelet-domain. The results of the experiment demonstrate that the new method not only outperforms the traditional algorithms on the aspects of PSNR (Peak Signal-to-Noise Ratio), MSE (Mean Square Error) and reconstruction vision effect, but also has the advantages of rapid convergence and easy extension.
In order to resolve the problems of discontented restoration effect and confined applying scope which exist in the current compressed video restoration algorithms, a novel method to get super-resolution images from lo...
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In order to resolve the problems of discontented restoration effect and confined applying scope which exist in the current compressed video restoration algorithms, a novel method to get super-resolution images from low-resolution compressed video is proposed in this paper. At first, a uniform model is presented and the restoration problem in the Bayesian framework is formulated under the MAP criterion, then the focus is put on the hybrid motion-compensation and transform coding schemes, at last the methods of getting the parameters are provided. The results of the simulation clearly demonstrate that our method not only has the properties of finer vision effect and wider applying scope, but also performs better than those of current classical algorithms in the aspects of Peak Signal Noise Ratio （PSNR） under the basis of the same condition.
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