This paper presents a new spatio-temporal motion estimation algorithm for video coding. The algorithm is based on optimization theory and consists of the strategies including 3D spatio-temporal motion vector prediction, modified one-at-a-time search scheme, and multiple update paths. The simulation results indicate our algorithm is better than other recently proposed ones under the same computational budget and is very close to full search. The low-cost feature and regular demand of computational resource make our algorithm suitable for VLSI implementation. The algorithm also makes single chip solution for high-definition coding feasible.
Motion-adaptive de-interlacing algorithm selects [4]. A more advanced technique to handle motion is motion from inter-field and intra-field interpolations according to estimation. Lee, Vissers and Liu [5] proposed a reducedmotion. Correct determination of motion information is complexity 3D motion estimation architecture which can be essential for this purpose. Fine textures, having high local used in MPEG4 and H.264.pixel variation, tend to cause false detection of motion. This paper proposed a texture detection mechanism utilizing In area of fine textures, which has high local variance or multiresolution technique to improve the correctness of frequency, pixels tend to have large gray level variation detection. A recursive 2-field algorithm is also proposed to within a small region. Slight motion or panning of camera reduce the memory cost in 4-field method. This algorithm would result in large pixel difference between two fields provides better perceptual visual quality than other motion which in turn causes erroneous motion detection. Detection adaptive de-interlacing as shown by theexperimental results.of this kind of texture can be used to set an adaptive threshold in motion detection to provide more accurate result.
This paper presents a frame level optimal rate is reduced. The multi-pass encoding scheme is generally not control scheme based on the proposed rate and distortion suitable for real-time applications due to the highly functions. A linear rate-quantizer model and a linear computational complexity and long encoding latency. Model distortion-quantizer model are proposed to perform ratebased rate control algorithms [2]-[6] allocate bit rate distortion optimization. The coefficients of rate distortion according to the closed-form solution of the rate distortion models are estimated by linear regression with the past rate models. These algorithms usually are more proper for IC distortion characteristics. We propose the two-stage strategy implementations and real-time applications. for rate-distortion optimization. First we use Lagrange multiplier optimization approach to obtain the closed-formIn this paper, we propose a one-pass real-time rate solution based on our rate distortion models. Then we take the control algorithm based on the proposed rate distortion inter-frame dependency into account to further adjust bit rate models and the two-stage optimization procedure. We allocation. We apply our optimal rate control algorithm to optimize the total quantization distortion of the group of H.264, and the proposed algorithm outperforms JVT-G012 pictures (GOP) by frame level rate control. The rest parts of rate control scheme in terms of average PSNR. this paper are organized as follows: In section II, we present the proposed linear rate and distortion models estimated by
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