Recent studies show that several FFT-based high-accuracy frequency estimation methods achieve very good performance. In this letter, we select three methods, which are the zero-padding, weighted multipoint interpolated DFT, and phase difference approximation respectively, and discuss the window selection for each method. Experiments show that the window selection primarily depends on the signal-to-noise ratio (SNR). As a result, the optimal window selection for each method and, reversely, the optimal selection of the estimation method for a specific window are discussed as a function of SNR. Consideration on the computational load and the resolution problem is also briefly discussed.

This letter proposes a motion information inferring scheme for multi-view video coding motivated by the idea that the aspect of motion vector between the corresponding positions in the neighboring view pair is quite similar. The proposed method infers the motion information from the corresponding macroblock in the neighboring view after RD optimization with the existing prediction modes. This letter presents evaluation showing that the method significantly enhances the efficiency especially at high bit rates.

Whereas the autocorrelation is frequently used for pitch estimation, the resultant estimates usually suffer from inaccuracy. Instead of upsampling, we can improve the accuracy of the estimates by applying polynomial interpolation to the autocorrelation directly. For that purpose, four kernels, which are interpolating quadratic, quadratic-B spline, cubic-B spline, and cubic convolution kernels respectively, have been compared. Experiments show that the cubic B spline kernel shows the best performance, a little inferior to the computationally intensive upsampling procedure. The quadratic B spline kernel shows also reasonable performance with the merit of the further reduced computational complexities compared with the cubic B spline kernel.