Motion compensated interpolation for subband coding of moving images

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (leaves 108-119).by Mark Daniel Polomski.M.S

Video Coding with Motion-Compensated Lifted Wavelet Transforms

This article explores the efficiency of motion-compensated three-dimensional transform coding, a compression scheme that employs a motion-compensated transform for a group of pictures. We investigate this coding scheme experimentally and theoretically. The practical coding scheme employs in temporal direction a wavelet decomposition with motion-compensated lifting steps. Further, we compare the experimental results to that of a predictive video codec with single-hypothesis motion compensation and comparable computational complexity. The experiments show that the 5/3 wavelet kernel outperforms both the Haar kernel and, in many cases, the reference scheme utilizing single-hypothesis motion-compensated predictive coding. The theoretical investigation models this motion-compensated subband coding scheme for a group of K pictures with a signal model for K motion-compensated pictures that are decorrelated by a linear transform. We utilize the Karhunen-Loeve Transform to obtain theoretical performance bounds at high bit-rates and compare to both optimum intra-frame coding of individual motion-compensated pictures and single-hypothesis motion-compensated predictive coding. The investigation shows that motion-compensated three-dimensional transform coding can outperform predictive coding with single-hypothesis motion compensation by up to 0.5 bits/sample

Visual Data Compression for Multimedia Applications

The compression of visual information in the framework of multimedia applications is discussed. To this end, major approaches to compress still as well as moving pictures are reviewed. The most important objective in any compression algorithm is that of compression efficiency. High-compression coding of still pictures can be split into three categories: waveform, second-generation, and fractal coding techniques. Each coding approach introduces a different artifact at the target bit rates. The primary objective of most ongoing research in this field is to mask these artifacts as much as possible to the human visual system. Video-compression techniques have to deal with data enriched by one more component, namely, the temporal coordinate. Either compression techniques developed for still images can be generalized for three-dimensional signals (space and time) or a hybrid approach can be defined based on motion compensation. The video compression techniques can then be classified into the following four classes: waveform, object-based, model-based, and fractal coding techniques. This paper provides the reader with a tutorial on major visual data-compression techniques and a list of references for further information as the details of each metho

Image Segmentation using Human Visual System Properties with Applications in Image Compression

In order to represent a digital image, a very large number of bits is required. For example, a 512 X 512 pixel, 256 gray level image requires over two million bits. This large number of bits is a substantial drawback when it is necessary to store or transmit a digital image. Image compression, often referred to as image coding, attempts to reduce the number of bits used to represent an image, while keeping the degradation in the decoded image to a minimum. One approach to image compression is segmentation-based image compression. The image to be compressed is segmented, i.e. the pixels in the image are divided into mutually exclusive spatial regions based on some criteria. Once the image has been segmented, information is extracted describing the shapes and interiors of the image segments. Compression is achieved by efficiently representing the image segments. In this thesis we propose an image segmentation technique which is based on centroid-linkage region growing, and takes advantage of human visual system (HVS) properties. We systematically determine through subjective experiments the parameters for our segmentation algorithm which produce the most visually pleasing segmented images, and demonstrate the effectiveness of our method. We also propose a method for the quantization of segmented images based on HVS contrast sensitivity, arid investigate the effect of quantization on segmented images

MASCOT : metadata for advanced scalable video coding tools : final report

The goal of the MASCOT project was to develop new video coding schemes and tools that provide both an increased coding efficiency as well as extended scalability features compared to technology that was available at the beginning of the project. Towards that goal the following tools would be used: - metadata-based coding tools; - new spatiotemporal decompositions; - new prediction schemes. Although the initial goal was to develop one single codec architecture that was able to combine all new coding tools that were foreseen when the project was formulated, it became clear that this would limit the selection of the new tools. Therefore the consortium decided to develop two codec frameworks within the project, a standard hybrid DCT-based codec and a 3D wavelet-based codec, which together are able to accommodate all tools developed during the course of the project

Fractional super-resolution of voxelized point clouds

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2021.Neste trabalho, apresentamos um método para super-resolver nuvens de pontos por um fator fracionário, utilizando um dicionário construído a partir de auto-similaridades presentes na versão subamostrada. Dada a geometria de uma nuvem de pontos subamostrada , juntamente com o correspondente fator de subamostragem , 1 < ≤ 2, o método proposto determina o conjunto de pontos que podem ter gerado e estima quais desses pontos, de fato, existem em (super resolução). Considerando que a geometria de uma nuvem de pontos é aproximadamente auto similar em diferentes escalas de subamostragem, cria-se um dicionário relacionando a configuração de ocupação da vizinhança com a ocupação de nós-filhos. O dicionário é obtido a partir de nova subamostragem da geometria de entrada utilizando o mesmo fator . Desta forma, leva-se em conta as irregularidades da subamostragem por fatores fracionários no desenvolvimento da super-resolução. A textura da nuvem de pontos é interpolada utilizando a média ponderada das cores de vizinhos adjacentes. Diversos conteúdos de diferentes fontes foram testados e resultados interessantes foram obtidos. Adicionalmente, apresentamos uma aplicação direta do método de super-resolução para melhorar a compressão de nuvens de pontos utilizando o codificador G-PCC do MPEG.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).We present a method to super-resolve voxelized point clouds downsampled by a fractional factor, using a lookup-table (LUT) constructed from self-similarities from their own downsampled neighbourhoods. Given a downsampled point cloud geometry , and its corresponding fractional downsampling factor , 1 < ≤ 2, the proposed method determines the set of positions that may have generated , and estimates which of these positions were indeed occupied (super resolution). Assuming that the geometry of a point cloud is approximately self-similar at different scales, a LUT relating downsampled neighbourhood configurations with children occupancy configurations can be estimated by further downsampling the input point cloud, and by taking into account the irregular children distribution derived from fractional downsampling. For completeness, we also interpolate texture by averaging colors from adjacent neighbour voxels. Extensive tests over different datasets are presented, and interesting results were obtained. We further present a direct application to improve point cloud compression using MPEG’s G-PCC codec

Low Bit-rate Color Video Compression using Multiwavelets in Three Dimensions

In recent years, wavelet-based video compressions have become a major focus of research because of the advantages that it provides. More recently, a growing thrust of studies explored the use of multiple scaling functions and multiple wavelets with desirable properties in various fields, from image de-noising to compression. In term of data compression, multiple scaling functions and wavelets offer a greater flexibility in coefficient quantization at high compression ratio than a comparable single wavelet. The purpose of this research is to investigate the possible improvement of scalable wavelet-based color video compression at low bit-rates by using three-dimensional multiwavelets. The first part of this work included the development of the spatio-temporal decomposition process for multiwavelets and the implementation of an efficient 3-D SPIHT encoder/decoder as a common platform for performance evaluation of two well-known multiwavelet systems against a comparable single wavelet in low bitrate color video compression. The second part involved the development of a motion-compensated 3-D compression codec and a modified SPIHT algorithm designed specifically for this codec by incorporating an advantage in the design of 2D SPIHT into the 3D SPIHT coder. In an experiment that compared their performances, the 3D motion-compensated codec with unmodified 3D SPIHT had gains of 0.3dB to 4.88dB over regular 2D wavelet-based motion-compensated codec using 2D SPIHT in the coding of 19 endoscopy sequences at 1/40 compression ratio. The effectiveness of the modified SPIHT algorithm was verified by the results of a second experiment in which it was used to re-encode 4 of the 19 sequences with lowest performance gains and improved them by 0.5dB to 1.0dB. The last part of the investigation examined the effect of multiwavelet packet on 3-D video compression as well as the effects of coding multiwavelet packets based on the frequency order and energy content of individual subbands