Approximate Hardware Architecture for Interpolation Filter of Versatile Video Coding

The new Versatile Video Coding (VVC) standard was recently developed to improve compression efficiency of previous video coding standards and to support new applications. This was achieved at the cost of an increase in the computational complexity of the encoder algorithms, which leads to the need to develop hardware accelerators and to apply approximate computing techniques to achieve the performance and power dissipation required for systems that encode video. This work proposes the implementation of an approximate hardware architecture for interpolation filters defined in the VVC standard targeting real-time processing of high resolution videos. The architecture is able to process up to 2560x1600 pixels videos at 30 fps with power dissipation of 23.9 mW when operating at a frequency of 522 MHz, with an average compression efficiency degradation of only 0.41% compared to default VVC video encoder software configuration.

An Adaptive Surface Interpolation Filter Using Cloth Simulation and Relief Amplitude for Airborne Laser Scanning Data

Separating point clouds into ground and nonground points is an essential step in the processing of airborne laser scanning (ALS) data for various applications. Interpolation-based filtering algorithms have been commonly used for filtering ALS point cloud data. However, most conventional interpolation-based algorithms have exhibited a drawback in terms of retaining abrupt terrain characteristics, resulting in poor algorithmic precision in these regions. To overcome this drawback, this paper proposes an improved adaptive surface interpolation filter with a multilevel hierarchy by using a cloth simulation and relief amplitude. This method uses three hierarchy levels of provisional digital elevation model (DEM) raster surfaces with thin plate spline (TPS) interpolation to separate ground points from unclassified points based on adaptive residual thresholds. A cloth simulation algorithm is adopted to generate sufficient effective initial ground seeds for constructing topographic surfaces with high quality. Residual thresholds are adaptively constructed by the relief amplitude of the examined area to capture complex landscape characteristics during the classification process. Fifteen samples from the International Society for Photogrammetry and Remote Sensing (ISPRS) commission are used to assess the performance of the proposed algorithm. The experimental results indicate that the proposed method can produce satisfying results in both flat areas and steep areas. In a comparison with other approaches, this method demonstrates its superior performance in terms of filtering results with the lowest omission error rate; in particular, the proposed approach retains discontinuous terrain features with steep slopes and terraces.

Multi-Rate Discrete-Time Signal Processing

Chapter 17 presents the multi-rate signal process, starting with explanations of the up-sampling and down-sampling procedures on a discrete signal in the time domain. The operations of a down-sampler (decimator) and an up-sampler (interpolator) are analysed in the frequency domain, emphasizing the problem of possible aliasing. Complex systems that include both up-sampling and down-sampling are analysed and the problem of complexity reduction is mentioned. The operation of systems that combine an interpolator and an interpolation filter, and a decimator and a decimation lowpass filter, is presented in the time and frequency domains. In particular, the problem of reducing the complexity of a multi-rate system is addressed, and a polyphase decomposition for both finite impulse response filters and infinite impulse response filters is offered as an efficient solution.

Spatial Structure-Related Sensory Landmarks Recognition Based on Long Short-Term Memory Algorithm

Indoor localization is the basis for most Location-Based Services (LBS), including consumptions, health care, public security, and augmented reality. Sensory landmarks related to the indoor spatial structures (such as escalators, stairs, and corners) do not rely on active signal transmitting devices and have fixed positions, which can be used as the absolute positioning information to improve the performance of indoor localization effectively without extra cost. Specific motion patterns are presented when users pass these architectural structures, which can be captured by mobile built-in sensors, including accelerometers, gyroscopes, and magnetometers, to achieve the recognition of structure-related sensory landmarks. Therefore, the recognition of these landmarks can draw on the mature methods of Human Activity Recognition (HAR) with improvements. To this end, we improved a Long Short-Term Memory (LSTM) neural network to recognize different kinds of spatial structure-related sensory landmarks. Labels of structural sensory landmarks were proposed, and data processing methods (including interpolation, filter, and window length) were used and compared to achieve the highest recognition accuracy of 99.6%.

Analysis of synchronous interpolated signals in Tactical Sensor Network-Visible light communication (TSN-VLC) link

Sampling frequency offset (SFO) is an important issue in the tactical sensor network (TSN) based visible light communication (VLC) systems in Tactical Sensor Network. A digital interpolation can be used to effectively compensate the SFO. In such case, oversampling at the receiver ADC is required to mitigate the aliasing effect due to imperfect DACs and nonlinearity of visible light sources that cause extra frequency components inside/outside the signal spectrum. The oversampling factor is mainly determined by the order of the digital interpolation filter and TSN links. The design of the TSN-VLC receiver incorporating the digital interpolation filter is vital as it affects not only the transmission performance but also the complexity of signal processing. To evaluate the feasibility of the digital interpolation-based SFO compensation schemes for cost-sensitive TSN applications. Based on the real-time VLC tactical sensor network, the comparison in the VLC-TSN transmission performance and DSP complexity between different interpolation-based SFO compensation schemes is analyzed.

High-Fidelity and High-Efficiency Digital Class-D Audio Power Amplifier

This study presents a high-fidelity and high-efficiency digital class-D audio power amplifier (CDA), which consists of digital and analog modules. To realize a compatible digital input, a fully digital audio digital-to-analog converter (DAC) is implemented on MATLAB and Xilinx System Generator, which consists of a 16x interpolation filter, a fourth-order four-bit quantized delta-sigma (ΔΣ) modulator, and a uniform-sampling pulse width modulator. The CDA utilizes the closed-loop negative feedback and loop-filtering technologies to minimize distortion. The audio DAC, which is based on a field-programmable gate array, consumes 0.128 W and uses 7100 LUTs, which achieves 11.2% of the resource utilization rate. The analog module is fabricated in a 0.18 µm BCD technology. The postlayout simulation results show that the CDA delivers an output power of 1 W with 93.3% efficiency to a 4 Ω speaker and achieves 0.0138% of the total harmonic distortion (THD) with a transient noise for a 1 kHz input sinusoidal test tone and 3.6 V supply. The output power reaches up to 2.73 W for 1% THD (with transient noise). The proposed amplifier occupies an active area of 1 mm2.