Improved Method to Select the Lagrange Multiplier for Rate-Distortion Based Motion Estimation in Video Coding

The motion estimation (ME) process used in the H.264/AVC reference software is based on minimizing a cost function that involves two terms (distortion and rate) that are properly balanced through a Lagrangian parameter, usually denoted as lambda(motion). In this paper we propose an algorithm to improve the conventional way of estimating lambda(motion) and, consequently, the ME process. First, we show that the conventional estimation of lambda(motion) turns out to be significantly less accurate when ME-compromising events, which make the ME process to perform poorly, happen. Second, with the aim of improving the coding efficiency in these cases, an efficient algorithm is proposed that allows the encoder to choose between three different values of lambda(motion) for the Inter 16x16 partition size. To be more precise, for this partition size, the proposed algorithm allows the encoder to additionally test lambda(motion) = 0 and lambda(motion) arbitrarily large, which corresponds to minimum distortion and minimum rate solutions, respectively. By testing these two extreme values, the algorithm avoids making large ME errors. The experimental results on video segments exhibiting this type of ME-compromising events reveal an average rate reduction of 2.20% for the same coding quality with respect to the JM15.1 reference software of H.264/AVC. The algorithm has been also tested in comparison with a state-of-the-art algorithm called context adaptive Lagrange multiplier. Additionally, two illustrative examples of the subjective performance improvement are provided.This work has been partially supported by the National Grant TEC2011-26807 of the Spanish Ministry of Science and Innovation.Publicad

Complexity management of H.264/AVC video compression.

The H. 264/AVC video coding standard offers significantly improved compression efficiency and flexibility compared to previous standards. However, the high computational complexity of H. 264/AVC is a problem for codecs running on low-power hand held devices and general purpose computers. This thesis presents new techniques to reduce, control and manage the computational complexity of an H. 264/AVC codec. A new complexity reduction algorithm for H. 264/AVC is developed. This algorithm predicts "skipped" macroblocks prior to motion estimation by estimating a Lagrange ratedistortion cost function. Complexity savings are achieved by not processing the macroblocks that are predicted as "skipped". The Lagrange multiplier is adaptively modelled as a function of the quantisation parameter and video sequence statistics. Simulation results show that this algorithm achieves significant complexity savings with a negligible loss in rate-distortion performance. The complexity reduction algorithm is further developed to achieve complexity-scalable control of the encoding process. The Lagrangian cost estimation is extended to incorporate computational complexity. A target level of complexity is maintained by using a feedback algorithm to update the Lagrange multiplier associated with complexity. Results indicate that scalable complexity control of the encoding process can be achieved whilst maintaining near optimal complexity-rate-distortion performance. A complexity management framework is proposed for maximising the perceptual quality of coded video in a real-time processing-power constrained environment. A real-time frame-level control algorithm and a per-frame complexity control algorithm are combined in order to manage the encoding process such that a high frame rate is maintained without significantly losing frame quality. Subjective evaluations show that the managed complexity approach results in higher perceptual quality compared to a reference encoder that drops frames in computationally constrained situations. These novel algorithms are likely to be useful in implementing real-time H. 264/AVC standard encoders in computationally constrained environments such as low-power mobile devices and general purpose computers

Long-Term Memory Motion-Compensated Prediction

Long-term memory motion-compensated prediction extends the spatial displacement vector utilized in block-based hybrid video coding by a variable time delay permitting the use of more frames than the previously decoded one for motion compensated prediction. The long-term memory covers several seconds of decoded frames at the encoder and decoder. The use of multiple frames for motion compensation in most cases provides significantly improved prediction gain. The variable time delay has to be transmitted as side information requiring an additional bit rate which may be prohibitive when the size of the long-term memory becomes too large. Therefore, we control the bit rate of the motion information by employing rate-constrained motion estimation. Simulation results are obtained by integrating long-term memory prediction into an H.263 codec. Reconstruction PSNR improvements up to 2 dB for the Foreman sequence and 1.5 dB for the Mother–Daughter sequence are demonstrated in comparison to the TMN-2.0 H.263 coder. The PSNR improvements correspond to bit-rate savings up to 34 and 30%, respectively. Mathematical inequalities are used to speed up motion estimation while achieving full prediction gain

Contributions to the solution of the rate-distorsion optimization problem in video coding

In the last two decades, we have witnessed significant changes concerning the demand of video codecs. The diversity of services has significantly increased, high definition (HD) and beyond-HD resolutions have become a reality, the video traffic coming from mobile devices and tablets is increasing, the video-on-demand services are now playing a prominent role, and so on. All of these advances have converged to demand more powerful standard video codecs, the more recent ones being the H.264/Advanced Video Coding (H.264/AVC) and the latest High Efficiency Video Coding (HEVC), both generated by the Joint Collaborative Team on Video Coding (JCT-VC), a partnership of the ITU-T Video Coding Expert Group (VCEG) and the ISO/IED Moving Picture Expert Group (MEPG). These two standards (and many others starting with the ITU-T H.261) rely on a hybrid model known as Differential Pulse Code Modulation (DPCM)/Discrete Cosine Transform (DCT) hybrid video coder, which involves a motion estimation and compensation phase followed by a transformation and quantization stages and an entropy coder. Moreover, each of these main subsystems is made of a number of interdependent and parametric modules that can be adapted to the particular video content. The main problem arising from this approach is how to choose as best as possible the combination of the different parametrizations to achieve the most efficient coding of the current content. To solve this problem, one of the solutions proposed (and the one adopted in both the H.264/AVC and the HEVC reference encoder implementations) is the process referred to as rate-distortion optimization, which chooses a parametrization of the encoder based on the minimization of a cost function that considers the trade-off between rate and distortion, weighted by a Lagrange multiplier (��) which has been empirically obtained for both the H.264/AVC and the HEVC reference encoder implementations, aiming to provide a robust solution for a variety of video contents. In this PhD. thesis, an exhaustive study of the influence of this Lagrangian parameter on different video sequences reveals that there are some common features that appear frequently in video sequences for which the adopted �� model (the reference model) becomes ineffective. Furthermore, we have found a notable margin of improvement in the coding efficiency of both coders when using a more adequate model for the Lagrangian parameter. Thus, contributions of this thesis are the following: (i) to prove that the reference Lagrangian model becomes ineffective in certain common situations; and (ii), propose generalized solutions to improve the robustness of the reference model, both for the H.264/AVC and the HEVC standards, obtaining important improvements in the coding efficiency. In both proposals, changes in the nature over the video sequence are taken into account, proposing models that adaptively consider the video content and minimize the increment in computational complexity.En las últimas dos décadas hemos sido testigos de importantes cambios en la demanda de codificadores de vídeo debido a múltiples factores: la diversidad de servicios se ha visto incrementada significativamente, la resolución high definition (HD) (e incluso mayores) se ha hecho realidad, el tráfico de vídeo procedente de dispositivos móviles y tabletas está aumentando y los servicios de vídeo bajo demanda son cada vez más comunes, entre otros muchos ejemplos. Todos estos avances convergen en la demanda de estándares de codificación de vídeo más potentes, siendo los más importantes el H.264/Advanced Video Coding (AVC) y el más reciente High Efficiency Video Coding (HEVC), ambos definidos por el Joint Collaborative Team on Video Coding (JCT-VC), una colaboraci´on entre el ITU-T Video Coding Expert Group (VCEG) y el ISO/IED Moving Picture Expert Group (MPEG). Estos dos estándares (y otros muchos, empezando con el ITU-T H.261) se basan en un modelo híbrido de codificador conocido como Differential Pulse Code Modulation (DPCM)/Discrete Cosine Transform (DCT), que está formado por una estimación y compensación de movimiento seguida de una etapa de transformación y cuantificación y un codificador entrópico. Además, cada uno de estos subsistemas está formado por un cierto número de módulos interdependientes y paramétricos que pueden adaptarse al contenido específico de cada secuencia de vídeo. El principal problema que surge de esta aproximación es cómo elegir de la forma más adecuada la combinación de las distintas parametrizaciones con el objetivo de alcanzar la codificación más eficiente posible del contenido que se está procesando. Para resolver este problema, una de las soluciones propuestas es el proceso conocido como optimización tasa-distorsión, que se encarga de elegir una parametrización para el codificador basada en la minimización de una función de coste que considera el compromiso existente entre la tasa y la distorsión, ponderado por un multiplicador de Lagrange (�) que ha sido obtenido de forma empírica para las implementaciones de referencia del codificador tanto del estándar H.264/AVC como del estándar HEVC, con el objetivo de proponer una solución robusta para distintos tipos de contenidos de vídeo. En esta tesis doctoral, un estudio exhaustivo de la influencia de este parámetro lagrangiano en distintas secuencias de vídeo revela que existen algunas características comunes que aparecen frecuentemente en secuencias de vídeo para las que el modelo � adoptado en las implementaciones de referencia resulta poco efectivo. Además, hemos encontrado un notable margen de mejora en la eficiencia de codificación de ambos codificadores usando un modelo más adecuado para este parámetro lagrangiano. Por consiguiente, las contribuciones de esta tesis son las que siguen: (i) probar que el modelo lagrangiano de referencia resulta inefectivo bajo ciertas situaciones comunes; y (ii), proponer soluciones generalizadas para mejorar la robustez del modelo de referencia, tanto en el caso de H.264/AVC como en el de HEVC, obteniendo mejoras importantes en eficiencia de codificación. En ambas propuestas se tienen en cuenta los cambios en la naturaleza del contenido de una secuencia de vídeo proponiendo modelos que se adaptan dinámicamente a dicho contenido variable y que tienen en cuenta el incremento en la complejidad computacional del codificador.Programa Oficial de Doctorado en Multimedia y ComunicacionesPresidente: José Prades Nebot.- Secretario: Carmen Peláez Moreno.- Vocal: Julián Cabrera Quesad

Motion compensation with minimal residue dispersion matching criteria

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnoloigia, 2016.Com a crescente demanda por serviços de vídeo, técnicas de compressão de vídeo tornaram-se uma tecnologia de importância central para os sistemas de comunicação modernos. Padrões para codificação de vídeo foram criados pela indústria, permitindo a integração entre esses serviços e os mais diversos dispositivos para acessá-los. A quase totalidade desses padrões adota um modelo de codificação híbrida, que combina métodos de codificação diferencial e de codificação por transformadas, utilizando a compensação de movimento por blocos (CMB) como técnica central na etapa de predição. O método CMB tornou-se a mais importante técnica para explorar a forte redundância temporal típica da maioria das sequências de vídeo. De fato, muito do aprimoramento em termos de e ciência na codificação de vídeo observado nas últimas duas décadas pode ser atribuído a refinamentos incrementais na técnica de CMB. Neste trabalho, apresentamos um novo refinamento a essa técnica. Uma questão central à abordagem de CMB é a estimação de movimento (EM), ou seja, a seleção de vetores de movimento (VM) apropriados. Padrões de codificação tendem a regular estritamente a sintaxe de codificação e os processos de decodificação para VM's e informação de resíduo, mas o algoritmo de EM em si é deixado a critério dos projetistas do codec. No entanto, embora praticamente qualquer critério de seleção permita uma decodi cação correta, uma seleção de VM criteriosa é vital para a e ciência global do codec, garantindo ao codi cador uma vantagem competitiva no mercado. A maioria do algoritmos de EM baseia-se na minimização de uma função de custo para os blocos candidatos a predição para um dado bloco alvo, geralmente a soma das diferenças absolutas (SDA) ou a soma das diferenças quadradas (SDQ). A minimização de qualquer uma dessas funções de custo selecionará a predição que resulta no menor resíduo, cada uma em um sentido diferente porém bem de nido. Neste trabalho, mostramos que a predição de mínima dispersão de resíduo é frequentemente mais e ciente que a tradicional predição com resíduo de mínimo tamanho. Como prova de conceito, propomos o algoritmo de duplo critério de correspondência (ADCC), um algoritmo simples em dois estágios para explorar ambos esses critérios de seleção em turnos. Estágios de minimização de dispersão e de minimização de tamanho são executadas independentemente. O codificador então compara o desempenho dessas predições em termos da relação taxa-distorção e efetivamente codifica somente a mais eficiente. Para o estágio de minimização de dispersão do ADCC, propomos ainda o desvio absoluto total com relação à média (DATM) como a medida de dispersão a ser minimizada no processo de EM. A tradicional SDA é utilizada como a função de custo para EM no estágio de minimização de tamanho. O ADCC com SDA/DATM foi implementado em uma versão modificada do software de referência JM para o amplamente difundido padrão H.264/AVC de codificação. Absoluta compatibilidade a esse padrão foi mantida, de forma que nenhuma modificação foi necessária no lado do decodificador. Os resultados mostram aprimoramentos significativos com relação ao codificador H.264/AVC não modificado.With the ever growing demand for video services, video compression techniques have become a technology of central importance for communication systems. Industry standards for video coding have emerged, allowing the integration between these services and the most diverse devices. The almost entirety of these standards adopt a hybrid coding model combining di erential and transform coding methods, with block-based motion compensation (BMC) at the core of its prediction step. The BMC method have become the single most important technique to exploit the strong temporal redundancy typical of most video sequences. In fact, much of the improvements in video coding e ciency over the past two decades can be attributed to incremental re nements to the BMC technique. In this work, we propose another such re nement. A key issue to the BMC framework is motion estimation (ME), i.e., the selection of appropriate motion vectors (MV). Coding standards tend to strictly regulate the coding syntax and decoding processes for MV's and residual information, but the ME algorithm itself is left at the discretion of the codec designers. However, though virtually any MV selection criterion will allow for correct decoding, judicious MV selection is critical to the overall codec performance, providing the encoder with a competitive edge in the market. Most ME algorithms rely on the minimization of a cost function for the candidate prediction blocks given a target block, usually the sum of absolute di erences (SAD) or the sum of squared di erences (SSD). The minimization of any of these cost functions will select the prediction that results in the smallest residual, each in a di erent but well de ned sense. In this work, we show that the prediction of minimal residue dispersion is frequently more e cient than the usual prediction of minimal residue size. As proof of concept, we propose the double matching criterion algorithm (DMCA), a simple two-pass algorithm to exploit both of these MV selection criteria in turns. Dispersion minimizing and size minimizing predictions are carried out independently. The encoder then compares these predictions in terms of rate-distortion performance and outputs only the most e cient one. For the dispersion minimizing pass of the DMCA, we also propose the total absolute deviation from the mean (TADM) as the measure of residue dispersion to be minimized in ME. The usual SAD is used as the ME cost function in the size minimizing pass. The DMCA with SAD/TADM was implemented in a modi ed version of the JM reference software encoder for the widely popular H.264/AVC coding standard. Absolute compliance to the standard was maintained, so that no modi cations on the decoder side were necessary. Results show signi cant improvements over the unmodi ed H.264/AVC encoder