Efficient Coding Method Research Articles

Efficient On-Board Compression for Arbitrary-Shaped Cloud-Covered Remote Sensing Images via Adaptive Filling and Controllable Quantization

Due to the fact that invalid cloud-covered regions in remote sensing images consume a considerable quantity of coding bit rates under the limited satellite-to-ground transmission rate, existing image compression methods suffer from low compression efficiency and poor reconstruction quality, especially in cloud-free regions which are generally regarded as regions of interest (ROIs). Therefore, we propose an efficient on-board compression method for remote sensing images with arbitrary-shaped clouds by leveraging the characteristics of cloudy images. Firstly, we introduce two novel spatial preprocessing strategies, namely, the optimized adaptive filling (OAF) strategy and the controllable quantization (CQ) strategy. Specifically, the OAF strategy fills each cloudy region using the contextual information at its inner and outer edge to completely remove the information of cloudy regions and minimize their coding consumption, which is suitable for images with only thick clouds. The CQ strategy implicitly identifies thin and thick clouds and rationally quantifies the data in cloudy regions to alleviate information loss in thin cloud-covered regions, which can achieve the balance between coding efficiency and reconstructed image quality and is more suitable for images containing thin clouds. Secondly, we develop an efficient coding method for a binary cloud mask to effectively save the bit rate of the side information. Our method provides the flexibility for users to choose the desired preprocessing strategy as needed and can be embedded into existing compression framework such as JPEG2000. Experimental results on the GF-1 dataset show that our method effectively reduces the coding consumption of invalid cloud-covered regions and significantly improve the compression efficiency as well as the quality of decoded images.

A Modulated Approach for Improving MFSK RADARS to Resolve Mutual Interference on Autonomous Vehicles (AVs).

This paper proposes a novel automotive radar waveform involving the theory behind M-ary frequency shift key (MFSK) radar systems. Along with the MFSK theory, coding schemes are studied to provide a solution to mutual interference. The proposed MFSK waveform consists of frequency increments throughout the range of 76 GHz to 81 GHz with a step value of 1 GHz. Instead of stepping with a fixed frequency, a triangular chirp sequence allows for static and moving objects to be detected. Therefore, automotive radars will improve Doppler estimation and simultaneous range of various targets. In this paper, a binary coding scheme and a combined transform coding scheme used for radar waveform correlation are evaluated in order to provide unique signals. AVs have to perform in an environment with a high number of signals being sent through the automotive radar frequency band. Efficient coding methods are required to increase the number of signals that are generated. An evaluation method and experimental data of modulated frequencies as well as a comparison with other frequency method systems are presented.

Efficient Geometry Surface Coding in V-PCC

In recent video-based point cloud compression (V-PCC), 3D point clouds are projected onto 2D images and compressed by High-Efficiency Video Coding (HEVC). However, HEVC was originally designed for natural visual signals, which is a suboptimal framework for point clouds. Therefore, there are still problems in geometry information compression in V-PCC: (1) The distortion based on the sum of squared error (SSE) in the existing rate-distortion optimization (RDO) is inconsistent with the geometric quality measurement; (2) The existing prediction cannot explore the fixed relationship between the corresponding far layer and near layer depth, which means that the far layer depth can be always not less than the corresponding near layer depth. In this paper, we present an efficient geometry surface coding (EGSC) method for V-PCC to address the problems. Firstly, an error projection (EP) model is designed to establish the relationship between the SSE-based distortion and the geometry quality metric. Secondly, an EP-based RDO is employed to improve the geometry information compression by estimating the point normals with gradients. Finally, an occupancy-map driven scheme is proposed to improve the prediction accuracy of merge modes. Experimental results show that the proposed method achieves an average of over 10% bit-rate saving compared with the V-PCC reference software.

Efficiency Analysis of Jaccard Similarity in Probabilistic Distribution Model

The inner probabilistic properties of the big data have a great impact on the performance of pattern recognition systems. Jaccard similarity (JS) is a most popular statistic metric used for cal-culating the similarity of objects in feature extraction process. The paper combines JS with probabil-istic distribution model to explore the effect of the inner properties of big data. It deduced the gener-alized form of JS for probabilistic model and determined the calculation method of JS for power-law and exponential distribution. Experiment observations showed that power-law distribution has high-er JS than the correspondent exponential distribution, which denotes that power-law probabilistic structure is a more efficient probability structure. The original normalized data in MNIST database exhibited a more power-law-like distribution and the randomly translated data exhibited a more exponential-like distribution. The MNIST data with power-law-like property has higher JS and are more efficient comparing to the translated data. Thus, these observations provide possible guidelines for efficient information coding and processing methods.

The DataScope: A Mixed-Initiative Architecture for Data Labeling

Machine learning promises many advantages, but achieving these promises requires methods that smooth the interaction between humans and machine learning. Machine learning systems require meticulous training on large, labeled datasets. Labeling data is a tedious expensive process, and many times requires complex human-judgment skills. Mixed-initiative designs divide the labor between the artificial agent and the human to make the task at hand more efficient and effective. This paper proposes a mixed-initiative method for efficient coding of video and image data in general and emotion data in particular. We integrate an unsupervised dimensionality reduction algorithm and the R Shiny platform to develop an interactive method that leverages human expertise to label the data more efficiently and effectively. The method, through the interactive web tool, allows the user to explore the data interactively, examine similarities and dissimilarities in the data, and label clusters of many images and video frames at once. The combination of the unsupervised learning algorithm and the R Shiny platform enables interactive exploration and annotation of high-dimensional, complicated data. This method can be used to annotate large data sets faster and can advance research in machine vision.

Compression of deep neural networks: bridging the gap between conventional-based pruning and evolutionary approach

Recently, many studies have been carried out on model compression to handle the high computational cost and high memory footprint brought by the implementation of deep neural networks. In this paper, model compression of convolutional neural networks is constructed as a multiobjective optimization problem with two conflicting objectives, reducing the model size and improving the performance. A novel structured pruning method called Conventional-based and Evolutionary Approaches Guided Multiobjective Pruning (CEA-MOP) is proposed to address this problem, where the power of conventional pruning methods is effectively exploited for the evolutionary process. A delicate balance in pruning rate and model accuracy has been automated achieved by a multiobjective optimization evolutionary model. First, an ensemble framework integrates pruning metrics to establish a codebook for further evolutionary operations. Then, an efficient coding method is developed to shorten the length of chromosome, thus ensuring its superior scalability. Finally, sensitivity analysis is automatically carried out to determine the upper bound of pruning rate for each layer. Notably, on CIFAR-10, CEA-MOP reduces more than 50% FLOPs on ResNet-110 and improves the relative accuracy. Moreover, on ImageNet, CEA-MOP reduces more than 50% FLOPs on ResNet-101 with negligible top-1 accuracy drop.

Stack Operation of Tensor Networks

The tensor network, as a factorization of tensors, aims at performing the operations that are common for normal tensors, such as addition, contraction, and stacking. However, because of its non-unique network structure, only the tensor network contraction is so far well defined. In this study, we propose a mathematically rigorous definition for the tensor network stack approach that compresses a large number of tensor networks into a single one without changing their structures and configurations. We illustrate the main ideas with the matrix product states based on machine learning as an example. Our results are compared with the for-loop and the efficient coding method on both CPU and GPU.

Efficient ADMM-Based Algorithms for Convolutional Sparse Coding

Convolutional sparse coding improves on the standard sparse approximation by incorporating a global shift-invariant model. The most efficient convolutional sparse coding methods are based on the alternating direction method of multipliers and the convolution theorem. The only major difference between these methods is how they approach a convolutional least-squares fitting subproblem. This letter presents a solution to this subproblem, which improves the efficiency of the state-of-the-art algorithms. We also use the same approach for developing an efficient convolutional dictionary learning method. Furthermore, we propose a novel algorithm for convolutional sparse coding with a constraint on the approximation error.

Method for coding positional coordinates of a frame-spline tensor in a mixed poliadic space

The need to improve the efficiency of the provision of video services for information support systems for the functioning of critical infrastructure facilities, including under conditions of information and cyber attacks from an opposing or competing side, is emphasized. Especially the research problem concerns the delivery of high-resolution dynamic video information resources using mobile infocommunication technologies, both ground-based and aerospace-based. The necessity of increasing the efficiency of the compact syntactic representation of the sequence of B-P frames for information technologies, process and transfer of dynamic video resources is substantiated. The advantages of the approach with respect to coding a sequence of frames of B-P types based on the construction of structural splines and their corresponding frame structures for differentiated blocks of frames in the transformable space are shown. To increase the amount of redundancy that can be potentially eliminated, it is proposed to form a set of frame splines for a dynamic sequence of TD-blocks. In this case, the statistical, psycho-visual and structural redundancy of the video sequence is reduced on the basis of identifying the corresponding patterns, both within frames and between them. The main technological approaches to the creation of a method for efficient coding of positional coordinates of single-element frame-spline tensors of a sequence of B-P frames on the basis of a two-pole mixed poliadic representation are revealed. It is shown that the integration of the created method for encoding a dynamic sequence of predicted video frames into the information technology for processing and transmitting video resources allows to increase its functioning efficiency in terms of such indicators as time delays for bringing video information, the integrity of the video information resource. Therefore, the quality of information support for the functioning of critical infrastructure systems is improved. that the integration of the created method for coding a dynamic sequence of predicted video frames into the information technology for processing and transmitting video resources allows to increase its efficiency in terms of such indicators as time delays for bringing video information, the integrity of the video information resource. Therefore, the quality of information support for the functioning of critical infrastructure systems is improved. that the integration of the created method for encoding a dynamic sequence of predicted video frames into the information technology for processing and transmitting video resources makes it possible to increase its efficiency in terms of such indicators as time delays for bringing video information, the integrity of the video information resource. Therefore, the quality of information support for the functioning of critical infrastructure systems is improved

Application of bar coding for digital watermarking of video sequences based on frequency transforms

Introduction: Owners of multimedia products face an important problem of protecting their digital data. An effective way to solve it is digital watermarking of video sequences. The challenge is the need to improve the digital watermark tolerance for transcoding when the data are transmitted via unprotected channels. Purpose: Development of method for embedding data into a video sequence which would have a higher tolerance for transcoding. Methods: We propose a novel method for embedding and extracting textual digital watermarks based on the bar coding and Arnold transform. Results: Blind marking schemes have been developed for digital video sequences in chromatic components, based on the discrete wavelet transform and discrete cosine transform. An experimental study has been conducted to check the stability of the proposed method using encoders x264 (AVC/H.264) and x265 (HEVC/H.265). The estimation of transcoding impact has shown that the frequency method based on wavelet decomposition has a high degree of stability. It was discovered during the experiments that for the cases of video transcoding by single-pass compression with a Constant Rate Factor not exceeding 26, the embedded textual information is fully restorable. Practical relevance: The developed method allows you to reliably embed or extract textual data from video sequences compressed using highly efficient coding methods during their transmission viaunprotected channels, providing copyright protection for multimedia product owners.

ІНФОРМАЦІЙНІ ПАРАМЕТРИ КОДОВИХ АНСАМБЛІВ, СИНТЕОВАНИХ НА ОСНОВІ ОДНОГО МОДУЛЯ

The advantages of digital methods of processing, displaying, storing and transmitting information. Currently, various conversion methods and efficient coding methods are used to increase the speed of information transfer, maintain high accuracy and provide the required latent accuracy. In particular, timer (temporary) signal constructions, which, in comparison with other coding methods, for example, positional (bitwise) coding, can reduce costs by more than two times. In the work, the information parameters of the code ensembles synthesized at a constant duration "m" are evaluated. Determined the conditions for the formation of a code ensemble and calculate the number of code dictionary implementations on a segment of a nyquist elements.In order to use the communication channel efficiently, the proposed increase in the entropy of the transmitted ensemble is due to the use of code sets with different number of information segments and at a constant length of the code word. A significant increase in the weight of the synthesized ensemble ensured an increase in the value of the module А0 =19 integer times K є 8:18 .The maximum values of the module are calculated in which the greatest number of code words is synthesized: At: КА0 =13, Np=8; КА0 =14, Np=10 КА0 =15, Np=15; КА0 =17, Np=16 КА0 =18, Np=10; КА0 =19, Np=6 КА0 =20, Np=1 For these КА0 values, the entropy value is H=3.269, which is less than the entropy of the Russian text H=4.35. In accordance with code words that satisfy the conditions of the quality equation. The methods and algorithms of reliable reception of code words under the influence of interference in the channel used were analyzed.Studies and calculations have shown that the use of temporary signal structures synthesized on the basis of a onemodule can significantly reduce the value of entropy for the transmission of Russian text.

An Improved Low-Power Coding for Serial Network-On-Chip Links

In the fast nanosilicon revolution era, network-on-chip (NoC) architecture offers a significant research solution to on-chip multiprocessor-based real-time applications. As the number of cores increases, power consumption of the resources of NoC also increases. Links are the major power dissipator in NoC architecture owing to switching activity of data bits communicated through them. The performance of data communication links in NoC is strongly dependent on the factor of power dissipation. An efficient coding method is needed to reduce both coupling and self-switching activity of data bits of NoC links. In this work, an improved low-power encoding algorithm for serial links is proposed to reduce switching transition for any random data pattern making them more suited to real-time applications. The proposed encoding algorithm is coded, simulated and verified its area and power performance using Synopsys tools utilizing UMC 90 nm technology. Experimental results have shown that it provides on average 48.83% of switching activity reduction for any real-time applications.

Two-Layer Near-Lossless HDR Coding Using Zero-Skip Quantization with Backward Compatibility to JPEG

We propose an efficient two-layer near-lossless coding method using an extended histogram packing technique with backward compatibility to the legacy JPEG standard. The JPEG XT, which is the international standard to compress HDR images, adopts a two-layer coding method for backward compatibility to the legacy JPEG standard. However, there are two problems with this two-layer coding method. One is that it does not exhibit better near-lossless performance than other methods for HDR image compression with single-layer structure. The other problem is that the determining the appropriate values of the coding parameters may be required for each input image to achieve good compression performance of near-lossless compression with the two-layer coding method of the JPEG XT. To solve these problems, we focus on a histogram-packing technique that takes into account the histogram sparseness of HDR images. We used zero-skip quantization, which is an extension of the histogram-packing technique proposed for lossless coding, for implementing the proposed near-lossless coding method. The experimental results indicate that the proposed method exhibits not only a better near-lossless compression performance than that of the two-layer coding method of the JPEG XT, but also there are no issue regarding the combination of parameter values without losing backward compatibility to the JPEG standard.

Most frequent mode for intra‐mode coding in video coding

The emerging versatile video coding (VVC) standard currently adopts 67 intra-prediction modes in order to improve the intra-prediction performance. The most probable mode (MPM) is used in video coding to encode the prediction mode efficiently based on the modes of the neighbouring blocks. Due to an increase in the number of intra-modes and increase in the resolution of the input sequence, it is necessary to efficiently encode the intra-mode of the current block. This Letter proposes an efficient intra-mode coding method extending MPM called most frequent mode (MFM), which exploits the number of occurrences of the modes in the neighbouring blocks. The proposed MFM derives the most frequent intra-mode. Then the derived MFM is signaled by a flag with a higher priority than MPM. Experimental results show that, compared to the test model of VVC (VTM), the proposed method gives up to 0.48% Bjotegaard-Delta-rate savings for the all-intra-configuration.

Generalizing Hamming+k data hiding by overlapped pixels

Matrix coding based data hiding (MCDH) using linear codes (syndrome coding) is an efficient coding method for steganographic schemes to improve their embedding efficiency. Hamming code data hiding (HDH) is a well-known MCDH using a covering function COV (1, n = 2k − 1, k). Afterwards, Hamming+ 1 DH (H1DH) was proposed with good embedding efficiency. However, these two previous approaches, HDH and H1DH, are not efficient for a large amount of messages. To tackle this problem, Yang et al.’s proposed Hamming+ k DH (Hk DH), which enhance the extra one embedded bit in H1DH to k embedded bits in the Hk DH. In this paper, we extended the Hk DH to the Hamming+ k with m overlapped pixels (Hk_mDH). The proposed Hk_mDH adopted pixel overlapping approach, optimal pixel adjustment process (OPAP), and Least Significant Bit (LSB) substitution. Experimental results demonstrate that our Hk_mDH has better embedding rate (ER) compared with previous schemes. In addition, we have proved that our Hk_mDH has excellent theoretical estimation of average mean square error.

A Joint Physical Layer Encryption and PAPR Reduction Scheme Based on Polar Codes and Chaotic Sequences in OFDM System

Channel coding and security are important in a communication system. The 5th generation (5G) mobile communication networks call for higher requirements of new coding technologies and encryption technologies. As an efficient coding method, polar codes have attracted more attention in recent years. Besides, the peak-to-average-power ratio (PAPR) is a major problem of the orthogonal frequency-division multiplexing (OFDM) system, which will significantly affect the performance of the OFDM system. In this paper, joint physical-layer encryption and PAPR reduction scheme is proposed, aiming to solve the PAPR problem and achieve high security of the transmission system. In this scheme, we utilize the key generation technology of wireless channels to get the initial value of chaotic sequences. Then, the chaotic sequences can be used to encrypt the information and reduce PAPR simultaneously. Moreover, we use the best information bits of polar codes to store the serial number index of chaotic sequences. The theoretic analysis and simulation results show that the proposed scheme can not only achieve high security in the physical layer but also reduce PAPR in the OFDM system without increasing system complexity and latency.

Fast coding method of metasurfaces based on 1D coding in orthogonal directions

Fast coding method of metasurfaces, based on 1D coding in orthogonal directions, is proposed in this paper. For the previous designed coding metasurfaces with M × N coding sequence, all the M × N codes need to be optimized as a whole, so that the optimized efficiency and flexibility are limited. In this regard, the coding metasurfaces are achieved via only designing the 1D coding sequences in orthogonal directions, and the coding sequences in the 2D plane can be derived by a binary addition algorithm of the two coding sequences. That means, for the M × N coding sequence, the number of coding elements that need to be optimized will be reduced from M × N to M + N. Thus, a faster optimizing method for coding metasurface design will be realized. To validate the method, 16 × 16 coding metasurfaces were designed by optimizing only two 1 × 16 random coding sequences. Both the simulation and experimental results of the designed coding metasurface demonstrated the coding metasurface design method and their excellent performance on mono-static and bi-static radar cross section reduction, which provides a more efficient coding method that allows more flexible manipulation of EM waves.

Two-Layer Lossless HDR Coding Using Histogram Packing Technique with Backward Compatibility to JPEG

An efficient two-layer coding method using the histogram packing technique with the backward compatibility to the legacy JPEG is proposed in this paper. The JPEG XT, which is the international standard to compress HDR images, adopts two-layer coding scheme for backward compatibility to the legacy JPEG. However, this two-layer coding structure does not give better lossless performance than the other existing methods for HDR image compression with single-layer structure. Moreover, the lossless compression of the JPEG XT has a problem on determination of the coding parameters; The lossless performance is affected by the input images and/or the parameter values. That is, finding appropriate combination of the values is necessary to achieve good lossless performance. It is firstly pointed out that the histogram packing technique considering the histogram sparseness of HDR images is able to improve the performance of lossless compression. Then, a novel two-layer coding with the histogram packing technique and an additional lossless encoder is proposed. The experimental results demonstrate that not only the proposed method has a better lossless compression performance than that of the JPEG XT, but also there is no need to determine image-dependent parameter values for good compression performance without losing the backward compatibility to the well known legacy JPEG standard.

Multiresolution coding of motion capture data for real-time multimedia applications

In this work, we present a novel and efficient method for coding of motion capture (MoCap) data obtained from recording of human actions. MoCap data is represented as hierarchies of joints and parameterized by translation and rotation of channels or degree-of-freedom (DOF) in a sequence of frames as a function of time. The proposed method approximates the MoCap data of each channel independently using multiresolution discrete wavelet transform (DWT). In order to improve the performance, a skeleton dependent quantization of wavelet coefficients is used that computes a local threshold of each joint based on a global threshold and depth of the joint in the hierarchy of joints. The multiresolution DWT based coding allows to control the bitrate and to decode (reconstruct) the single instance of compressed MoCap data into multiple instances from high to low resolution (quality). We also compared the performance of proposed method with recent and state of the art methods. The proposed method yields smaller storage space and faster encoding time. The method is well suitable for real-time multimedia applications due to its low time and space requirements.

A noise immunity controlled quantum teleportation protocol

With the advent of the Internet and information and communication technology, quantum teleportation has become an important field in information security and its application areas. This is because quantum teleportation has the ability to attain a timely secret information delivery and offers unconditional security. And as such, the field of quantum teleportation has become a hot research topic in recent years. However, noise has serious effect on the safety of quantum teleportation within the aspects of information fidelity, channel capacity and information transfer. Therefore, the main purpose of this paper is to address these problems of quantum teleportation. Firstly, in order to resist collective noise, we construct a decoherence-free subspace under different noise scenarios to establish a two-dimensional fidelity quantum teleportation models. And also create quantum teleportation of multiple degree of freedom, and these models ensure the accuracy and availability of the exchange of information and in multiple degree of freedom. Secondly, for easy preparation, measurement and implementation, we use super dense coding features to build an entangled quantum secret exchange channel. To improve the channel utilization and capacity, an efficient super dense coding method based on ultra-entanglement exchange is used. Thirdly, continuous variables of the controlled quantum key distribution were designed for quantum teleportation; in addition, we perform Bell-basis measurement under the collective noise and also prepare the storage technology of quantum states to achieve one-bit key by three-photon encoding to improve its security and efficiency. We use these two methods because they conceal information, resist a third party attack and can detect eavesdropping. Our proposed methods, according to the security analysis, are able to solve the problems associated with the quantum teleportation under various noise environments.