Study on applications of motion estimation and motion compensation on television

制度:新 ; 文部省報告番号:乙1962号 ; 学位の種類:博士(工学) ; 授与年月日:2004/12/16 ; 早大学位記番号:新388

High performance shift invariant motion estimation and compensation in wavelet domain video compression

The contributions of this dissertation are in the development of two new interrelated approaches to video data compression: 1) A level-refined motion estimation and subband compensation method for the effective motion estimation and motion compensation. 2) A shift-invariant sub-decimation decomposition method in order to overcome the deficiency of the decimation process in estimating motion due to its shift-invariant property of wavelet transform. The enormous data generated by digital videos call for an intense need of efficient video compression techniques to conserve storage space and minimize bandwidth utilization. The main idea of video compression is to reduce the interpixel redundancies inside and between the video frames by applying motion estimation and motion compensation (MEMC) in combination with spatial transform coding. To locate the global minimum of the matching criterion function reasonably, hierarchical motion estimation by coarse to fine resolution refinements using discrete wavelet transform is applied due to its intrinsic multiresolution and scalability natures

On-device Frame Interpolation for High Frame Rate Video Conferencing

This disclosure describes techniques to use frame interpolation to provide high quality, high frame rate video streams displayed on a mobile device in applications such as a video conference with low power consumption. A video stream having a low frame rate is received at a mobile device. On-device frame interpolation is performed using techniques such as motion estimation and motion compensation, voxel flow, or machine learning to determine a new frame between consecutive frames of the video stream. The video stream including the interpolated frames is displayed on the mobile device at a higher frame rate, providing smooth motion

A noise detection, noise-motion separation and a cancer recognition theory and algorithm

In this thesis we describe a noise detection and a motion-noise separation algorithm, as well as the stochastic properties of the noise. The difference between corresponding pixels subject to one type of noise, of two frames, has mean vector equal to (0,0,0), and variance covariance matrix with relatively small variances, for the (R, G, B) difference values. The other type of noise is a result of disturbance of the light equilibrium due to motion in neighboring or nearby pixels. In this type of noise the mean of the difference is non-zero. Every pixel not included in the one type of noise or the other is part of the motion set between the two frames. The pixels are organized in macroblocks, so macroblocks containing pixels with motion are applied motion estimation and motion compensation methods first and subsequently the difference between the corresponding macroblocks of the two frames is obtained; This thesis furthermore describes an algorithm of cancer recognition of ultrasound images. (Abstract shortened by UMI.)

IBVC: Interpolation-driven B-frame Video Compression

Learned B-frame video compression aims to adopt bi-directional motion estimation and motion compensation (MEMC) coding for middle frame reconstruction. However, previous learned approaches often directly extend neural P-frame codecs to B-frame relying on bi-directional optical-flow estimation or video frame interpolation. They suffer from inaccurate quantized motions and inefficient motion compensation. To address these issues, we propose a simple yet effective structure called Interpolation-driven B-frame Video Compression (IBVC). Our approach only involves two major operations: video frame interpolation and artifact reduction compression. IBVC introduces a bit-rate free MEMC based on interpolation, which avoids optical-flow quantization and additional compression distortions. Later, to reduce duplicate bit-rate consumption and focus on unaligned artifacts, a residual guided masking encoder is deployed to adaptively select the meaningful contexts with interpolated multi-scale dependencies. In addition, a conditional spatio-temporal decoder is proposed to eliminate location errors and artifacts instead of using MEMC coding in other methods. The experimental results on B-frame coding demonstrate that IBVC has significant improvements compared to the relevant state-of-the-art methods. Meanwhile, our approach can save bit rates compared with the random access (RA) configuration of H.266 (VTM). The code will be available at https://github.com/ruhig6/IBVC.Comment: Submitted to IEEE TCSV

AN EFFICIENT MOTION ESTIMATION ALGORITHM BASED ON PARTICLE SWARM OPTIMIZATION

The PSO algorithm reduce the search points without the degradation of the image quality. It provides accurate motion estimation with very low complexity in the context of video estimation. This algorithm is capable of reducing the computational complexity of block matching process. This algorithm maintains high estimation accuracy compared to the full search method. The critical component in most block-based video compression system is Motion Estimation because redundancy between successive frames of video sequence allows for compression of video data. These algorithms are used to reduce the computational requirement by checking only some points inside the search window, while keeping a good error performance when compared with Full Search and Diamond search algorithm. This algorithm should maintain high estimation accuracy compared to the Full search method and Diamond search algorithm. Here by using the PSO algorithm could get a high accuracy in the block-based motion estimation