Detection of dirt impairments from archived film sequences : survey and evaluations

Film dirt is the most commonly encountered artifact in archive restoration applications. Since dirt usually appears as a temporally impulsive event, motion-compensated interframe processing is widely applied for its detection. However, motion-compensated prediction requires a high degree of complexity and can be unreliable when motion estimation fails. Consequently, many techniques using spatial or spatiotemporal filtering without motion were also been proposed as alternatives. A comprehensive survey and evaluation of existing methods is presented, in which both qualitative and quantitative performances are compared in terms of accuracy, robustness, and complexity. After analyzing these algorithms and identifying their limitations, we conclude with guidance in choosing from these algorithms and promising directions for future research

Statistical framework for video decoding complexity modeling and prediction

Video decoding complexity modeling and prediction is an increasingly important issue for efficient resource utilization in a variety of applications, including task scheduling, receiver-driven complexity shaping, and adaptive dynamic voltage scaling. In this paper we present a novel view of this problem based on a statistical framework perspective. We explore the statistical structure (clustering) of the execution time required by each video decoder module (entropy decoding, motion compensation, etc.) in conjunction with complexity features that are easily extractable at encoding time (representing the properties of each module's input source data). For this purpose, we employ Gaussian mixture models (GMMs) and an expectation-maximization algorithm to estimate the joint execution-time - feature probability density function (PDF). A training set of typical video sequences is used for this purpose in an offline estimation process. The obtained GMM representation is used in conjunction with the complexity features of new video sequences to predict the execution time required for the decoding of these sequences. Several prediction approaches are discussed and compared. The potential mismatch between the training set and new video content is addressed by adaptive online joint-PDF re-estimation. An experimental comparison is performed to evaluate the different approaches and compare the proposed prediction scheme with related resource prediction schemes from the literature. The usefulness of the proposed complexity-prediction approaches is demonstrated in an application of rate-distortion-complexity optimized decoding

A fully scalable wavelet video coding scheme with homologous inter-scale prediction

In this paper, we present a fully scalable wavelet-based video coding architecture called STP-Tool, in which motion-compensated temporal-filtered subbands of spatially scaled versions of a video sequence can be used as a base layer for inter-scale predictions. These predictions take place in a pyramidal closed-loop structure between homologous resolution data, i.e., without the need of spatial interpolation. The presented implementation of the STP-Tool architecture is based on the reference software of the Wavelet Video Coding MPEG Ad-Hoc Group. The STP-Tool architecture makes it possible to compensate for some of the typical drawbacks of current wavelet-based scalable video coding architectures and shows interesting objective and visual results even when compared with other wavelet-based or MPEG-4 AVC/H.264-based scalable video coding systems

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

State-of-the-Art and Trends in Scalable Video Compression with Wavelet Based Approaches

3noScalable Video Coding (SVC) differs form traditional single point approaches mainly because it allows to encode in a unique bit stream several working points corresponding to different quality, picture size and frame rate. This work describes the current state-of-the-art in SVC, focusing on wavelet based motion-compensated approaches (WSVC). It reviews individual components that have been designed to address the problem over the years and how such components are typically combined to achieve meaningful WSVC architectures. Coding schemes which mainly differ from the space-time order in which the wavelet transforms operate are here compared, discussing strengths and weaknesses of the resulting implementations. An evaluation of the achievable coding performances is provided considering the reference architectures studied and developed by ISO/MPEG in its exploration on WSVC. The paper also attempts to draw a list of major differences between wavelet based solutions and the SVC standard jointly targeted by ITU and ISO/MPEG. A major emphasis is devoted to a promising WSVC solution, named STP-tool, which presents architectural similarities with respect to the SVC standard. The paper ends drawing some evolution trends for WSVC systems and giving insights on video coding applications which could benefit by a wavelet based approach.partially_openpartially_openADAMI N; SIGNORONI. A; R. LEONARDIAdami, Nicola; Signoroni, Alberto; Leonardi, Riccard

Motion estimation and signaling techniques for 2D+t scalable video coding

We describe a fully scalable wavelet-based 2D+t (in-band) video coding architecture. We propose new coding tools specifically designed for this framework aimed at two goals: reduce the computational complexity at the encoder without sacrificing compression; improve the coding efficiency, especially at low bitrates. To this end, we focus our attention on motion estimation and motion vector encoding. We propose a fast motion estimation algorithm that works in the wavelet domain and exploits the geometrical properties of the wavelet subbands. We show that the computational complexity grows linearly with the size of the search window, yet approaching the performance of a full search strategy. We extend the proposed motion estimation algorithm to work with blocks of variable sizes, in order to better capture local motion characteristics, thus improving in terms of rate-distortion behavior. Given this motion field representation, we propose a motion vector coding algorithm that allows to adaptively scale the motion bit budget according to the target bitrate, improving the coding efficiency at low bitrates. Finally, we show how to optimally scale the motion field when the sequence is decoded at reduced spatial resolution. Experimental results illustrate the advantages of each individual coding tool presented in this paper. Based on these simulations, we define the best configuration of coding parameters and we compare the proposed codec with MC-EZBC, a widely used reference codec implementing the t+2D framework