Compression Distortion Research Articles

Compression-Dependent Transform-Domain Downward Conversion for Block-Based Image Coding.

Transform-domain downward conversion (TDDC) for image coding is usually implemented by discarding some high-frequency components from each transformed block. As a result, a block of fewer coefficients is formed, and a lower compression cost is achieved due to the coding of only a few low-frequency coefficients. In this paper, we focus on the design of a new TDDC-based coding method by using our proposed interpolation-compression directed filtering (ICDF) and error-compensated scalar quantization (ECSQ), leading to the compression-dependent TDDC (CDTDDC)-based coding. More specifically, ICDF is first used to convert each macro-block into an coefficient block. Then, this coefficient block is compressed with ECSQ, resulting in a smaller compression distortion for those pixels that locate at some specific positions of a macro-block. We select these positions according to the 4:1 uniform sub-sampling lattice and use the pixels locating at them to reconstruct the whole macro-block through an interpolation. The proposed CDTDDC-based coding can be applied to compress both grayscale and color images. More importantly, when it is used in the color image compression, it offers not only a new solution to reduce the data-size of chrominance components but also a higher compression efficiency. Experimental results demonstrate that applying our proposed CDTDDC-based coding to compress still images can achieve a significant quality gain over the existing compression methods.

Video analytical coding: When video coding meets video analysis

Leveraging on the properties of human visual system, most of the well-designed video coding standards utilize rate–distortion optimization techniques by maximizing a fidelity cost function (e.g., peak signal noise ratio, PSNR) under an available bit rate budget constrain. However, a huge amount of video data is consumed by computers rather than by human beings in several application scenarios. In view of this, this paper proposes a new coding framework called video analytical coding (VAC) for video analysis. We use the term “analytical distortion” to denote the difference of video analysis performance when video quality degrades and analytical distortion is estimated by compression distortion. Meanwhile, we develop a new rate–analytical-distortion optimization (RADO) method to trade off the bit rate and the analytical distortion. Specifically, we consider moving object detection as the analysis task and develop a rate analytical distortion (RAD) model and a quantization parameter adaptation strategy for video coding, where the analytical distortion is related to the object detection performance represented as F1-measure. Experimental results show that the performance of the video analysis task can be significantly improved (up to 40% reduction of analytical distortion).

A new enhancement to avoid video distortion in wireless multihop networks

The protocols of typical routing algorithms which are designed for the wireless networks long back are specifically application oriented. Taking consideration at present, with the increase in the usage of the wireless networks the problem we are facing is video traffic. The very important thing is to maintain a good quality of video. At present users are opting videos in high quality that are to be delivered smoothly into their devices. The nature of video is changed due to 1) Because of the compression distortion occurs at the source. 2) With both interference and the errors induced on wireless channels distortion occurs. Hence, in this paper we work for the reduction of the distortion that occurs in video traffic. In order to overcome this problem we opted a wireless network in which the flow of application contains video traffic. For the clients the reduction of the distortion is very difficult. We cannot minimize the video distortions by using the link quality based routing measures. To understand this we construct an analytical framework first, then on the video distortions for accessing the impact. By using an analytical framework we design a routing measure for the reduction of distortion. With our experiment results we evaluate that our protocol is best for the reduction of video distortion and also for the reduction of the experience of user de-gradations.

Content Adaptive Lagrange Multiplier Selection for Rate-Distortion Optimization in 3-D Wavelet-Based Scalable Video Coding.

Rate-distortion optimization (RDO) plays an essential role in substantially enhancing the coding efficiency. Currently, rate-distortion optimized mode decision is widely used in scalable video coding (SVC). Among all the possible coding modes, it aims to select the one which has the best trade-off between bitrate and compression distortion. Specifically, this tradeoff is tuned through the choice of the Lagrange multiplier. Despite the prevalence of conventional method for Lagrange multiplier selection in hybrid video coding, the underlying formulation is not applicable to 3-D wavelet-based SVC where the explicit values of the quantization step are not available, with on consideration of the content features of input signal. In this paper, an efficient content adaptive Lagrange multiplier selection algorithm is proposed in the context of RDO for 3-D wavelet-based SVC targeting quality scalability. Our contributions are two-fold. First, we introduce a novel weighting method, which takes account of the mutual information, gradient per pixel, and texture homogeneity to measure the temporal subband characteristics after applying the motion-compensated temporal filtering (MCTF) technique. Second, based on the proposed subband weighting factor model, we derive the optimal Lagrange multiplier. Experimental results demonstrate that the proposed algorithm enables more satisfactory video quality with negligible additional computational complexity.

A Spatio-Temporal Perceptual Quality Index Measuring Compression Distortions of Three-Dimensional Video

Objective video quality assessment (VQA) of stereoscopic three-dimensional (3-D) video plays a vital role in the application of video compression and transmission. This letter presents an efficient full-reference metric, called 3-D perceptual quality index (3-D-PQI), to measure video compression distortion of stereoscopic videos. In the metric, local video compression distortions in left and right view are measured in both spatial and temporal channels by considering contrast and motion masking effect. Then, a stereo saliency based pooling strategy is used to accumulate local spatial and temporal distortions. Finally, 3-D-PQI is derived from texture energy based fusion of distortion measurement of left and right view. A verification test of the proposed metric is conducted on publicly available stereoscopic VQA databases, which shows that 3-D-PQI is superior to other VQA metrics with respect to correlation against subjective quality judgment.

Perceptual video quality metric for compression artefacts: from two‐dimensional to omnidirectional

In this study, the perceptual video quality (PVQ) for the vogue 360-degree video with compression artefacts viewed on the visual reality (VR) head-mounted display (HMD) is obtained for the first time by an elaborately designed subjective experiment. The characteristic of the PVQ of omnidirectional (360-degree) video on the VR HMD and PC monitor is then investigated. The PVQ on the HMD is found to be linearly related to the video coding quality (VCQ) on the PC monitor. A quality evaluation model is then proposed based on the mapping formula and a new assessment parameter, where the impact of the video resolution and display device is involved. In this way, the traditional video quality assessment metrics for two-dimensional video can be extended to assess the PVQ of the 360-degree video viewed on the HMD. At last, the video structural similarity metric is taken as an example to predict the input of the proposed model, i.e. the VCQ of the 360-degree video. Experimental results demonstrate that the proposed model can effectively and conveniently solve the challenge of PVQ assessment for the 360-degree video with compression distortions on the HMD.

Intensified peak-to-average power ratio of high-speed coupled signals in data center connections

The peak-to-average power ratio (PAPR) of a next generation data center optoelectronic communication system is analyzed. A new challenge of ultrabroadband signals transmission over coupled printed transmission lines (PTLs) is introduced for the case of separated design of the optical module and on-board electronics. PAPR enhancement models are developed for transmission of ultrabroadband signals over coupled PTLs, due to enhanced coupling impairments. High instantaneous peak power values may lead to compression and nonlinear distortions due to the limited dynamic range of the communication system components. The analysis, which is verified by Monte Carlo simulations, reveals that the instantaneous PAPR increases significantly.

Content‐based bitrate model for perceived compression distortion evaluation of mobile video services

A novel bitrate model with low complexity is proposed for perceived compression distortion assessment of mobile video with low resolution, which is extremely useful in intermediate network nodes for quality monitoring. Without fully decoding, parameters are extracted by bitstream analysing, such as bitrate, frame type, quantisation parameter, DCT coefficient, motion vector. Bitrate is regarded as an essential parameter meanwhile the bitrate–MOS curve is determined by video content. Respectively, spatial factor is estimated using quantisation parameter and DCT coefficient and temporal factor is estimated using motion vector. Apart from bitrate, the spatial and temporal factors, which reflect the characteristic of video content, are considered in the proposed model to obtain a more accurate evaluation. Experimental results show that the overall performance of proposed model significantly outperforms that of the other five bitrate models in terms of widely used performance criteria, including the Pearson correlation coefficient (PCC), the Spearman rank-order correlation coefficient (SROCC), the root-mean-squared error (RMSE) and the outlier ratio (OR).

Objective Video Quality Assessment Based on Perceptually Weighted Mean Squared Error

Object quality assessment for compressed video is critical to various video compression systems that are essential in the video delivery and storage. Although mean squared error (MSE) is computationally simple, it may not be accurate to reflect the perceptual quality of compressed videos, which are also affected dramatically by the characteristics of the human visual system (HVS), such as contrast sensitivity, visual attention, and masking effect. In this paper, a video quality metric is proposed based on perceptually weighted MSE. A low-pass filter is designed to model the contrast sensitivity of the HVS with the consideration of visual attention. The imperceptible distortion is adaptively removed in the salient and nonsalient regions. To quantitatively measure the masking effect, the randomness of video content is proposed in both the spatial and temporal domains. Since the masking effect highly depends on the regularity of structure and motion in the spatial and temporal directions, the video signal is modeled as a linear dynamic system, and the prediction error of future frames from previous frames is used as randomness to measure the significance of masking. The relation is investigated between MSE and perceptual quality scores across various contents, and a masking modulation model is proposed to compensate the impact of the masking effect on the MSE. The performance of the proposed quality metric is validated on three video databases with various compression distortions. The experimental results demonstrate that the proposed algorithm outperforms other benchmark quality metrics.

An Enhanced Run-Length Encoding Compression Method for Telemetry Data

AbstractThe telemetry data are essential in evaluating the performance of aircraft and diagnosing its failures. This work combines the oversampling technology with the run-length encoding compression algorithm with an error factor to further enhance the compression performance of telemetry data in a multichannel acquisition system. Compression of telemetry data is carried out with the use of FPGAs. In the experiments there are used pulse signals and vibration signals. The proposed method is compared with two existing methods. The experimental results indicate that the compression ratio, precision, and distortion degree of the telemetry data are improved significantly compared with those obtained by the existing methods. The implementation and measurement of the proposed telemetry data compression method show its effectiveness when used in a high-precision high-capacity multichannel acquisition system.

Study of Temporal Effects on Subjective Video Quality of Experience.

HTTP adaptive streaming is being increasingly deployed by network content providers, such as Netflix and YouTube. By dividing video content into data chunks encoded at different bitrates, a client is able to request the appropriate bitrate for the segment to be played next based on the estimated network conditions. However, this can introduce a number of impairments, including compression artifacts and rebuffering events, which can severely impact an end-user's quality of experience (QoE). We have recently created a new video quality database, which simulates a typical video streaming application, using long video sequences and interesting Netflix content. Going beyond previous efforts, the new database contains highly diverse and contemporary content, and it includes the subjective opinions of a sizable number of human subjects regarding the effects on QoE of both rebuffering and compression distortions. We observed that rebuffering is always obvious and unpleasant to subjects, while bitrate changes may be less obvious due to content-related dependencies. Transient bitrate drops were preferable over rebuffering only on low complexity video content, while consistently low bitrates were poorly tolerated. We evaluated different objective video quality assessment algorithms on our database and found that objective video quality models are unreliable for QoE prediction on videos suffering from both rebuffering events and bitrate changes. This implies the need for more general QoE models that take into account objective quality models, rebuffering-aware information, and memory. The publicly available video content as well as metadata for all of the videos in the new database can be found at http://live.ece.utexas.edu/research/LIVE_NFLXStudy/nflx_index.html.

Comparative Performance Evaluation of Three Image Compression Algorithms

The advent of computer and internet has brought about massive change to the ways images are being managed. This revolution has resulted in changes in image processing and management as well as the huge space requirement for images’ uploading, downloading, transferring and storing nowadays. In guiding against this huge space requirement, images need to be compressed before either storing or transmitting. Several algorithms or techniques on image compression had been developed in literature. In this study, three of these image compression algorithms were developed using MATLAB codes. The three algorithms developed are discrete cosine transform (DCT), discrete wavelet transform (DWT) and set partitioning in hierarchical tree (SPIHT). In order to ascertain which of them is most appropriate for image storing and transmission, comparative performance evaluations were conducted on the three developed algorithms using five performance indices. The results of the comparative performance evaluations show that the three algorithms are effective in image compression but with different efficiency rates. In addition, the comparative performance evaluations results show that DWT has the highest compression ratio and distortion level while the corresponding values for SPIHT is the lowest with those of DCT fall in-between. Also, the results of the study show that the lower the mean square error and the higher the peak signal-to-noise-ratio, the lower the distortion level in the compressed image.

Spatiotemporal distributions of plasma and optical field during the interaction between ultra-short laser pulses and water nanodroplets

The transient changes of free electron density distribution and light field intensity during the interaction between the femtosecond Gaussian laser pulses and millimeter scale water droplets are studied. Based on the nonlinear Maxwell's equations and the ionization rate equation, a transient coupled model is proposed to describe the laser plasma produced in water droplet. The changes of electron density and light field with time are obtained by the finite element method. The calculation results show that the laser induced breakdown threshold in the droplet is about 2 TW/cm2, one quarter of that in a boundaryless water medium under the same condition. We find that the region of plasma generated in the droplet will move along the laser direction at first, however, when the incident laser intensity becomes larger, it will move in the direction opposite to the laser beam propagation and the plasma shielded effect becomes more obvious. The laser beam converged by the droplet focuses outside the droplet, and its power density is five times larger than that of the incident laser. There happen the laser pulse duration compression and waveform distortion at the focus point due to the plasma absorption, and the absorption energy increases with the laser intensity increasing and reaches a saturation finally. We expect the model and calculation results to be able to be used for the study of laser pulse propagation in cloud or rain, the precision control of droplet by laser or eye surgery by laser, and other laser technology applications.

Virtual-View-Assisted Video Super-Resolution and Enhancement

A 3-D multiview video gives users an experience that is different from that provided by a traditional video; however, it puts a huge burden on limited bandwidth resources. Mixed-resolution video in a multiview system can alleviate this problem by using different video resolutions for different views. However, to reduce visual uncomfortableness and to make this video format more suitable for free-viewpoint television, the low-resolution (LR) views need to be super-resolved to the target full resolution. In this paper, we propose a virtual-view-assisted super-resolution algorithm, where the inter-view similarity is used to determine whether the missing pixels in the super-resolved frame need to be filled by virtual-view pixels or by spatial interpolated pixels. The decision mechanism is steered by the texture characteristics of the neighbors of each missing pixel. Furthermore, the inter-view similarity is used, on the one hand, to enhance the quality of the virtual-view-copied pixels by compensating the luminance difference between different views and, on the other hand, to enhance the original LR pixels in the super-resolved frame by reducing their compression distortion. Thus, the proposed method can recover the details in regions with edges while maintaining good quality at smooth areas by properly exploiting the high-quality virtual-view pixels and the directional correlation of pixels. The experimental results demonstrate the effectiveness of the proposed approach with a peak signal-to-noise ratio gain of up to 3.85 dB.

Wavelets‐based smoothness comparisons for volume data

In this study, the authors describe an objective smoothness assessment method for volume data. The metric can predict the extent of the difference in smoothness between a reference model, which may not be of perfect quality, and a distorted version. The proposed metric is based on the wavelet characterisation of Besov function spaces. The comparison of Besov norms between two models can resolve the global and local differences in smoothness between them. Experimental results from volume datasets with smoothing and sharpening operations demonstrate its effectiveness. By comparing direct volume rendered images, the experimental results show that the proposed smoothness index correlates well with human perceived vision. Finally, the metric can help the analyse compression distortions when they compare volume data with different smoothness.

Compressed image quality metric based on perceptually weighted distortion.

Objective quality assessment for compressed images is critical to various image compression systems that are essential in image delivery and storage. Although the mean squared error (MSE) is computationally simple, it may not be accurate to reflect the perceptual quality of compressed images, which is also affected dramatically by the characteristics of human visual system (HVS), such as masking effect. In this paper, an image quality metric (IQM) is proposed based on perceptually weighted distortion in terms of the MSE. To capture the characteristics of HVS, a randomness map is proposed to measure the masking effect and a preprocessing scheme is proposed to simulate the processing that occurs in the initial part of HVS. Since the masking effect highly depends on the structural randomness, the prediction error from neighborhood with a statistical model is used to measure the significance of masking. Meanwhile, the imperceptible signal with high frequency could be removed by preprocessing with low-pass filters. The relation is investigated between the distortions before and after masking effect, and a masking modulation model is proposed to simulate the masking effect after preprocessing. The performance of the proposed IQM is validated on six image databases with various compression distortions. The experimental results show that the proposed algorithm outperforms other benchmark IQMs.

Subjective and Objective Video Quality Assessment of 3D Synthesized Views With Texture/Depth Compression Distortion.

The quality assessment for synthesized video with texture/depth compression distortion is important for the design, optimization, and evaluation of the multi-view video plus depth (MVD)-based 3D video system. In this paper, the subjective and objective studies for synthesized view assessment are both conducted. First, a synthesized video quality database with texture/depth compression distortion is presented with subjective scores given by 56 subjects. The 140 videos are synthesized from ten MVD sequences with different texture/depth quantization combinations. Second, a full reference objective video quality assessment (VQA) method is proposed concerning about the annoying temporal flicker distortion and the change of spatio-temporal activity in the synthesized video. The proposed VQA algorithm has a good performance evaluated on the entire synthesized video quality database, and is particularly prominent on the subsets which have significant temporal flicker distortion induced by depth compression and view synthesis process.

EPR investigation of local structure for the [Mn(H2O)6]2+cluster in M(ClO4)2· 6H2O:Mn2+(M = Cd, Hg) systems at different temperatures

Local lattice structure distortion studies of the octahedral Mn 2+ center in M(ClO 4 ) 2 · 6H 2 O:Mn 2+ (M = Cd, Hg) systems have been performed systematically based on the diagonalization of the complete energy matrices of electron-electron repulsion, spin-orbit coupling and trigonal ligand-field interaction for a d 5 configuration ion in a trigonal ligand field. From the EPR calculation, the local structure distortion parameters R and θ are determined, respectively. Results show that the local lattice structure around a trigonal Mn 2+ center has a compressed distortion along the crystalline C 3 axis. The compression distortion may be ascribed to the fact that the radius of the Mn 2+ ion is smaller than that of the Hg 2+ ion and the Cd 2+ ion. The local lattice structure parameters for Mn 2+ in M(ClO 4 ) 2 · 6H 2 O:Mn 2+ (M = Cd, Hg) systems are determined at liquid-nitrogen temperature and room temperature.

Blind Sharpness Prediction Based on Image-Based Motion Blur Analysis

For high bit rate video, it is important to acquire the video contents with high resolution, the quality of which may be degraded due to the motion blur from the movement of an object(s) or the camera. However, conventional sharpness assessments are designed to find focal blur caused either by defocusing or by compression distortion targeted for low bit rates. To overcome this limitation, we present a no-reference framework of a visual sharpness assessment (VSA) for high-resolution video based on the motion and scene classification. In the proposed framework, the accuracy of the sharpness estimation can be improved via pooling weighted by the visual perception from the object and camera movements and by the strong influence from the region with the highest sharpness. Based on the motion blur characteristics, the variance and the contrast over the spectral domain are used to quantify the perceived sharpness. Moreover, for the VSA, we extract the highly influential sharper regions and emphasize them by utilizing the scene adaptive pooling. Based on the subjective results, we demonstrate that the VSA can measure the video sharpness more accurately than other sharpness measurements for high-resolution video.

Error Resilient SPIHT Coded Grayscale Image transmission over MIMO System

In this paper, we propose Error Resilient SPIHT coded MIMO system to address the issue of image transmission and reception over noisy Rayleigh Fading channel. Set Partitioning in Hierarchical Trees (SPIHT) is chosen as the compression algorithm since it offers the lossless compression and excellent rate distortion in noiseless environment. SPIHT encoded data is modulated in the manner that it will provide Unequal Error Protection (UEP) to achieve error resilience. In proposed method, SPIHT encoded data is divided into the low priority stream (LP) and the high priority stream (HP) to achieve UEP and as a result it yields high PSNR value. These streams are modulated using MQAM modulation scheme and transmitted over Multiple Input Multiple Output (MIMO) system to achieve better diversity. The adaptive value of M is determined by the proposed algorithm. Simulation results depicts that PSNR of received images are better as compared to that reported by Fowdur et al. [12].