1,754 research outputs found

    Velocity Dealiased Spectral Estimators of Range Migrating Targets using a Single Low-PRF Wideband Waveform

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    Wideband radars are promising systems that may provide numerous advantages, like simultaneous detection of slow and fast moving targets, high range-velocity resolution classification, and electronic countermeasures. Unfortunately, classical processing algorithms are challenged by the range-migration phenomenon that occurs then for fast moving targets. We propose a new approach where the range migration is used rather as an asset to retrieve information about target velocitiesand, subsequently, to obtain a velocity dealiased mode. More specifically three new complex spectral estimators are devised in case of a single low-PRF (pulse repetition frequency) wideband waveform. The new estimation schemes enable one to decrease the level of sidelobes that arise at ambiguous velocities and, thus, to enhance the discrimination capability of the radar. Synthetic data and experimental data are used to assess the performance of the proposed estimators

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

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    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

    Localized temporal decorrelation for video compression

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    Many of the current video compression algorithms perform analysis and coding operations in a block-wise manner. Most of them use a motion compensated DCT algorithm as the basis. Many other codecs, mostly academic and in their infancy and known as Second Generation techniques, utilize region and contour based and model based techniques. Unfortunately, these second-generation methods have not been successful in gaining widespread acceptance in both the standards and the consumer world. Many of them require specialized computationally intensive software and/or hardware. Due to these shortcomings, current block based methods have been finetuned to get better performance at even very low bit rates (sub 64 kbps). Block based motion estimation is the principal mechanism used to compensate for motion between frames in an image sequence. Although current algorithms are fast and quite effective, they fail in compensating for uncovered background areas in a frame. Solutions such as hierarchical motion estimation schemes do not work very well since there is no reference in past, and in some cases, future frames for an uncovered background resulting in the block being transmitted as an intra frame (which requires the most bandwidth among all type of blocks). This thesis intro duces an intermediate stage, which compensates for these isolated uncovered areas. The intermediate stage uses a localized decorrelation technique to reduce frame to frame temporal redundancies. The algorithm can be easily incorporated into exist ing systems to achieve an even better performance and can be easily extended as a scalable video coding architecture. Experimental results show that the algorithm, used in conjunction with motion estimation, is quite effective in reducing temporal redundancies

    Motion Scalability for Video Coding with Flexible Spatio-Temporal Decompositions

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    PhDThe research presented in this thesis aims to extend the scalability range of the wavelet-based video coding systems in order to achieve fully scalable coding with a wide range of available decoding points. Since the temporal redundancy regularly comprises the main portion of the global video sequence redundancy, the techniques that can be generally termed motion decorrelation techniques have a central role in the overall compression performance. For this reason the scalable motion modelling and coding are of utmost importance, and specifically, in this thesis possible solutions are identified and analysed. The main contributions of the presented research are grouped into two interrelated and complementary topics. Firstly a flexible motion model with rateoptimised estimation technique is introduced. The proposed motion model is based on tree structures and allows high adaptability needed for layered motion coding. The flexible structure for motion compensation allows for optimisation at different stages of the adaptive spatio-temporal decomposition, which is crucial for scalable coding that targets decoding on different resolutions. By utilising an adaptive choice of wavelet filterbank, the model enables high compression based on efficient mode selection. Secondly, solutions for scalable motion modelling and coding are developed. These solutions are based on precision limiting of motion vectors and creation of a layered motion structure that describes hierarchically coded motion. The solution based on precision limiting relies on layered bit-plane coding of motion vector values. The second solution builds on recently established techniques that impose scalability on a motion structure. The new approach is based on two major improvements: the evaluation of distortion in temporal Subbands and motion search in temporal subbands that finds the optimal motion vectors for layered motion structure. Exhaustive tests on the rate-distortion performance in demanding scalable video coding scenarios show benefits of application of both developed flexible motion model and various solutions for scalable motion coding
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