Low Error Approximate Absolute Difference Hardware

The progress of VLSI technology towards deep sub-micron feature sizes, e.g., sub-100 nanometer technology, has created a growing impact of hardware defects and fabrication process variability, which lead to reductions in yield rate. To address these problems, a new approach, system-level error tolerance (ET), has been recently introduced. Considering that a significant percentage of the entire chip production is discarded due to minor imperfections, this approach is based on accepting imperfect chips that introduce imperceptible/acceptable system-level degradation; this leads to increases in overall effective yield. In this paper, we investigate the impact of hardware faults on the video compression performance, with a focus on the motion estimation (ME) process. More specifically, we provide an analytical formulation of the impact of single and multiple stuck-at-faults within ME computation. We further present a model for estimating the system-level performance degradation due to such faults, which can be used for the error tolerance based decision strategy of accepting a given faulty chip. We also show how different faults and ME search algorithms compare in terms of error tolerance and define the characteristics of search algorithm that lead to increased error tolerance. Finally, we show that different hardware architectures performing the same metric computation have different error tolerance characteristics and we present the optimal ME hardware architecture in terms of error tolerance. While we focus on ME hardware, our work could also applied to systems (e.g., classifiers, matching pursuits, vector quantization) where a selection is made among several alternatives (e.g., class label, basis function, quantization codeword) based on which choice minimizes an additive metric of interest.

Although the fast ME/DE provides significant complexity reduction, a high-throughput hardware architecture is required for real-time ME/DE in MVC. Without a dedicated hardware, ME/DE for MVC in real-time mobile application is unfeasible. Therefore, in addition to our fast ME/DE algorithm we propose a novel motion and disparity estimation hardware architecture designed to provide real-time MVC encoding for up to four views HD1080p (1920 × 1080) based on the proposed fast ME/DE algorithm. Firstly, we are going to start presenting a high-level architectural template description. The architectural template, presented in Sect. 5.1, will give the required basis for a better understanding of the proposed architecture.

High throughput, heavy bandwidth requirement, huge on-chip memory consumption, and complex data flow control are major challenges in high definition integer motion estimation hardware implementation. This paper proposes an efficient very large scale integration architecture for integer multi-resolution motion estimation based on optimized algorithm. There are three major contributions in this paper. First, this paper proposes a hardware friendly multi-resolution motion estimation algorithm well-suited for high definition video encoder. Second, parallel processing element (PE) array structure is proposed to implement three-level hierarchical motion estimation, only 256PEs are enough for one reference frame real-time high definition motion estimation by efficient PE reuse. Third, efficient on-chip reference pixel buffer sharing mechanism between integer and fractional motion estimation is proposed with almost 50% SRAM saving and memory bandwidth reduction. The proposed multi-resolution motion estimation algorithm reached a good balance between complexity and performance with rate distortion optimized variable block size motion estimation support. Also, we have achieved moderate logic circuit and on-chip SRAM consumption. The proposed architecture is well-suited for all MPEG-like video coding standards such as H.264, audio video coding standard, and VC-1.

Motion estimation is the biggest part of any video encoding system since it could significantly affect the encoding time and output quality. Until now, several motion estimation algorithms that have the fast motion estimation and a good PSNR are proposed. However these are not considered an embedded system processor using SDRAM as a video frame memory. In this paper, we propose new fast predictive block matching algorithm, named predictive directional rectangular zonal search. Comparing with existing algorithms, it has not only similar output quality, but more efficient operating with SDRAM. It makes possible to design a hardware motion estimator into a compact one. A motion estimation hardware block that is based on the proposed algorithm for H.263 and MPEG-4 video encoder, is implemented by 0.3μm 1.2 V CMOS technology.

In this paper, an embedded hardware architecture for low bit depth representation based motion estimation method is proposed. The proposed hardware architecture can easily be integrated to the microprocessor systems thanks to the industry standard interface. Thus, the developed core has a structure that can be easily utilized as a sub component of state of the art video coding systems. Furthermore, the proposed motion estimation hardware architecture novel to this work. The reference motion estimation algorithm is based on the matching of the truncated Gray coded bit planes within an adaptive search range other than the conventional full search approach and it also includes an early termination mechanism to further shorten the search time.

Introduction:Power is an important variable to evaluate performance. With the increasing of devices for the power measurement, it is simple to associate certain watts to the running Functional Threshold Power measured in watts (rFTPw) as indicates Vance (2016). Affirming that the estimation of the power through accelerometry, can revolutionize the training of running.The main goal of this study was to find the most appropriate test for the determination of rFTPw. Material and methods:9 recreational triathletes participated in the study (22.9 + 4.8 years). All the tests were carried out with a minimum of 24 hours of rest between each test carried out in an athletics track measuring the running power data with Stryd Summit footpod (Stryd, Boulder, CO, USA). Results:The T 3 min -9 min was the one that presented a lower average error with respect to the rFTPw M for power and pace. Conclusions:T 3 min – 9 min could be the best alternative without taking into account the distance or duration of competition. Because that rFTPw changes depending of the duration of each test. It would not be valid to use the watts associated to Critical Speed (CS) obtained in the test T 3 MT. Being that it supposes a greater average error regarding the rFTPw M in power and pace. The T 30 min could be an alternative when calculating the rFTPw with the data obtained in a training or competition of the same duration. The tests with the lowest average error in the external variable power are the ones with the lowest error in pace. Although the pace would remain the main variable to control the external load in running.

Operative repair of complex conditions such as esophageal atresia and tracheoesophageal fistula (EA/TEF) is technically demanding, but few training opportunities exist outside the operating theater for surgeons to attain these skills. Learning them during surgery on actual neonates where the stakes are high, margins for error narrow, and where outcomes are influenced by technical expertise, is problematic. There is an increasing demand for high-fidelity simulation that can objectively measure performance. We developed such a simulator to measure force and motion reliably, allowing quantitative feedback of technical skill. A 3D-printed simulator for thoracoscopic repair of EA/TEF was instrumented with motion and force tracking components. A 3D mouse, inertial measurement unit (IMU), and optical sensor that captured force and motion data in four degrees of freedom (DOF) were calibrated and verified for accuracy. The 3D mouse had low average relative errors of 2.81%, 3.15%, and 6.15% for 0mm, 10mm offset in Y, and 10mm offset in X, respectively. This increased to - 23.5% at an offset of 42mm. The optical sensors and IMU displayed high precision and accuracy with low SDs and average relative errors, respectively. These parameters can be a useful measurement of performance for thoracoscopic EA/TEF simulation prior to surgery. Graphical abstract Inclusion of sensors into a high-fidelity simulator design can produce quantitative feedback which can be used to objectively asses performance of a technically difficult procedure. As a result, more surgical training can be done prior to operating on actual patients in the operating theater.

This work describes a parallelizable optical flow field estimator based upon a modified batch version of the Self-Organizing Map (SOM). This estimator handles the ill-posedness in gradient-based motion estimation via a novel combination of regression and self-organization. The aperture problem is treated using an algebraic framework that partitions motion estimates obtained from regression into two sets: one (set Hc) containing motion estimates with high confidence and another (set Hp) with low confidence. The self-organization step uses a uniquely designed pair of sets: training set (Q = Hc) and the initial weights set (\({W=H_c \cup H_p}\)). It is shown that with this specific choice of training and initial weights sets, the interpolation of flow vectors is achieved primarily due to the regularization property of the SOM. Moreover, the computationally involved step of finding the winner unit in SOM simplifies to indexing into a 2D array making the algorithm highly scalable. To preserve flow discontinuities at occlusion boundaries, we have designed an anisotropic neighborhood function for SOM that uses a novel optical flow constraint equation residual-based distance measure. A multi-resolution or pyramidal approach is used to estimate large motion. As self-organization based motion estimation is computationally intense, parallel processing on graphics processing units is used for speedup. As the algorithm is data (rather datum) parallel, with sufficient number of computing cores, the implementation of the estimator can be made real time. With the available ground truth from Middlebury database, error metrics like average angular error and average end point error are computed and are shown to be comparable with other leading techniques.

We propose a fast subpixel motion estimation algorithm for the H.264 advanced video coding (AVC) standard. The algorithm utilizes the correlation of the spatial interpolation effect on the full-pixel motion estimation best matches between different block sizes in order to reduce the computational cost of the overall motion-estimation process. Experimental results show that the proposed algorithm significantly reduces the CPU cycles in the various motion estimation schemes by up to 16% with similar rate-distortion performance when weighed up against the H.264/AVC standard.

Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms (BMA) for bringing down the complexity in the computation and has also got better attention in many algorithms that are very effective for very large scale integration (VLSI) systems for bringing down the complexity. These BMA algorithms are relatively easy to implement which can give solutions that are suboptimal even if the entire search has not been performed. The entire search is high in terms of cost of computation that prevents it from being applied in the systems of VLSI. A novel and fast motion estimation based algorithm known as charged system search (CSS) and full search algorithm (FSA) for multipliers of low power and for H.264 encoders is proposed. The CSS is used in all fields of optimization and is well suited for most domains and does not require any gradient information. The results have proved that proposed FSA has better performance.

The new trends in multimedia and especially in video applications demand the best possible quality, among with low bandwidth and memory usage. While video compression has been used for many decades, now is of even greater significance, particularly in the 4K and 8K UHD standards. In addition, the most time consuming and computationally expensive part of video compression, is the calculation of the objects' movement between successive frames, a procedure known as Motion Estimation. Our purpose in this paper was to create an embedded system which implements a Motion Estimation unit that is being controlled and fed by an ARM CPU. For that reason we used the Xilinx Zynq platform, which provides great flexibility and can be used to effectively evaluate an embedded system prototype. Our experimental results illustrate that it is perfectly feasible to implement fast and reliable accelerators, especially for multimedia applications, in a platform such as Xilinx Zynq.

An enhanced constrained one-bit transform (C1BT)-based fast motion estimation (ME) method is proposed. Binary transform-based ME identifies the proper motion vector by transforming the 8-bit pixels in the original image into a low bit depth of the bit plane, substantially reducing the computational complexity and facilitating hardware implementation by using the number of non-matching points (NNMPs) instead of the sum of absolute difference (SAD). However, a motion block size is N × N , therefore the dynamic range of NNMP (0 ≤ NNMP ≤ N × N ) is decreased to 1/256 compared to that of the SAD with 8-bit images (0 ≤ SAD ≤ 256 × N × N ). The higher the NNMP between the current bit plane and the previous bit plane, the more probable that it will be the block most similar to each other. Therefore, the matching error criterion of NNMP is extended to improve ME performance. Experimental results show that the proposed algorithm improves the performance of ME accuracy by 0.27, 0.38 and 0.67 dB compared to the C1BT-based ME, two-bit transform (2BT)-based ME and 1BT-based ME, respectively.

This paper proposes a motion estimation scheme to reduce the computational complexity of multilayer motion estimation for scalable video coding. Based on the result of the motion estimation of the lower resolution layer referred to as base layer, we developed a new approach for exploring the search range of the enhancement layer with high coding efficiency. This approach is based on the activity defined as the absolute difference between the motion vector predictor and the final motion vector. Based on the correlation of the activities between neighboring layers, an inter-layer activity model was developed using a curve-fitted linear equation to exploit the activity in the base layer for deciding the search center and the search range of the enhancement layer. Each activity pair in the neighboring layers is used to associate the relevant macroblock to one of two groups; boundary region and interior region. The base-layer motion vector predictor is basically selected over all the activity regions; for each activity region, the proposed motion estimation algorithm decides whether to include the median motion vector predictor or not. Minimal sufficient search range is also decided from the inter-layer activity prediction factor that is adjusted to the given sequence. The proposed scheme reduced the execution time of motion estimation by 99.26% at the cost of 1.56% bit-rate increase and 0.048 dB peak signal-to-noise ratio (PSNR) decrease on average compared with the conventional full-search algorithm. The fast full-search block matching algorithm can also be incorporated to obtain the extra CPU time reduction in the motion estimation process. By adopting the fast full-search block matching algorithm (FFSBMA) in JSVM reference software, the CPU time was reduced by up to 91.84% and the memory bandwidth was reduced by 90% at the sacrifice of 1.27% bit-rate increase and 0.041 dB PSNR decrease on average compared with the FFSBMA only.

This study explores the potential of utilizing weathered basalt waste, discarded from basalt stone quarrying, as a resource for producing efficient adsorbents to remove Fe (III) and Zn (II) from aqueous and real wastewater. Raw weathered basalt (RWB), and its calcined derivatives at 750 °C for 3 h (CWB-750) and at 950 °C for 1 h with activated carbon impregnation (CWB/AC-950), were prepared and characterized. Characterization using XRD, FTIR, SEM, and surface area analyzer revealed that calcination improved porosity and surface area with some privilege for CWB/AC-950. CWB/AC-950 revealed remarkable removal efficiency for Fe (III) at a pH value of 5, achieving 98.30%, closely matching that of RWB (98.00%), and outperforming CWB-750 (96.20%). In contrast, RWB exhibited the highest removal capacity for Zn (II) at a pH value of 6, with an efficiency of 55%, surpassing both CWB-750 and CWB/AC-950, which achieved approximately 36%. For both contaminants, Pseudo-2nd-order equation (R2 > 0.98) provided a superior fit, showcasing favorable sorption process by all the addressed materials. The Fe(III) sorption data for all the investigated materials were better described by the Freundlich (FL) model compared to the Langmuir (LM) model. Similarly, the Zn(II) sorption data for the calcined derivatives (CWB-750 and CWB/AC-950) were well-explained by the FL model. These findings are supported by the very high determination coefficients (R2 > 0.96) and significantly lower average relative error (ARE) values (8.66 and 13.69) compared to those obtained from the LM model (55.99 and 189.25, orderly). In contrast, for RWB, despite the very high R2 values (> 0.98) for both models, neither adequately captured the Zn(II) sorption behavior, as evidenced by the exceptionally high ARE values (52.67 and 161.19 for LM and FL, respectively). These findings are supported by the very high determination coefficients (R2 > 0.96) and significantly lower average relative error (ARE) values compared to those obtained from the LM model. In contrast, for RWB, despite the very high R2 values (> 0.98) for both models, neither adequately captured the Zn(II) sorption behavior, as evidenced by the exceptionally high ARE values (52.67 and 161.19 for LM and FL, respectively). The remediation mechanism of both Fe (III) and Zn (II) by all adsorbents was not exclusively governed by inter-particle diffusion. Eventually, these findings highlight the sustainable potential of repurposing RWB waste and its calcined derivatives for water remediation applications.

We investigate the packet-level scheduling for the downlink of multiple-input multiple-output (MIMO) multi-user systems using beamforming. We consider the traffic arrival process and different packet lengths. We tackle low-complex practical implementation that provides low average packet transmission delay and bit error rates (BER) to users. We propose a work-conserving scheduling scheme that considers different users guarantees (heterogeneous users). We implement and compare different MIMO schedulers at the packet level. Simulations show the low average packet transmission delay and bit error rate of our proposed scheduler.