Identification of neuropathogenic Varicellovirus equidalpha1 as a potential cause of respiratory disease outbreaks among horses in North Xinjiang, China, from 2021-2023.

BACKGROUND: Varicellovirus equidalpha1 (formerly Equid alphaherpesvirus 1, EqAHV-1) is among the most important viruses responsible for respiratory disease outbreaks among horses throughout the world. No reports to date have detailed the association between EqAHV-1 and respiratory disease among horses in China. This study described one such outbreak among a population of horses in north Xinjiang that occurred from April 2021 - May 2023. RESULTS: qPCR revealed that EqAHV-1 was detectable in all samples and this virus was identified as a possible source of respiratory disease, although a limited subset of these samples were also positive for EqAHV-2, EqAHV-4, and EqAHV-5. In total, three EqAHV-1 strains responsible for causing respiratory illness in horses were isolated successfully, and full-length ORF33 sequence comparisonsand phylogenetic analyses indicated that these isolates may have originated from EqAHV-1 strains detected in Yili horse abortions. ORF30 sequence data additionally suggested that these strains were neuropathic, as evidenced by the presence of a guanine residue at nucleotide position 2254 corresponding to the aspartic acid present at position 752 in the DNA polymerase encoded by this virus. CONCLUSION: This study is the first report of an outbreak of respiratory disease among horses in China caused by EqAHV-1. ORF30 sequence characterization revealed that these EqAHV-1 strains harbored a neuropathogenic genotype. Given the detection of this virus in horses suffering from respiratory disease, concern is warranted with respect to this neuropathogenic EqAHV-1 outbreak.

HMGB1 Release Induced by EV71 Infection Exacerbates Blood-Brain Barrier Disruption via VE-cadherin Phosphorylation.

PURPOSE: EV71 (Enterovirus 71) is a major causative agent of the outbreaks of HFMD (hand, foot, and mouth disease), which is associated with neurological damage caused by permeability disruption of BBB (blood-brain barrier). HMGB1 (high-mobility group box 1) is a widely expressed nuclear protein that triggers host inflammatory responses. Our work aimed to explore the function of HMGB1 in EV71 infection and its contributions to EV71-related BBB damage. METHODS: HeLa cells, HT-29 cells and AG6 mice were used to explore the translocation of HMGB1 in EV71 infection in vitro and in vivo. The roles of released HMGB1 on EV71 replication and associated inflammatory cytokines were investigated using recombinant HMGB1 in HeLa cells. The mechanisms of released HMGB1 in EV71-induced BBB injury were explored using recombinant HMGB1 and anti-HMGB1 neutralizing antibodies in monolayer HCMECs (immortalized human brain microvascular endothelial cells) and AG6 mice brain. RESULTS: EV71 induced HMGB1 nucleocytoplasmic translocation and extracellular release in vitro and in vivo. Released HMGB1 acted as an inflammatory mediator in EV71 infection rather than affecting viral replication in vitro. Released HMGB1 disrupted BBB integrity by enhancing VE-cadherin phosphorylation at tyrosine 685 in HCMECs, and reducing total VE-cadherin levels in HCMECs and AG6 mice in EV71 infection. And released HMGB1 induced an increase in activated astrocytes. Neutralization of HMGB1 reversed the increased endothelial hyperpermeability and phosphorylation of VE-cadherin in HCMECs. CONCLUSION: The inflammatory mediator HMGB1 released by EV71 exacerbated BBB disruption by enhancing VE-cadherin phosphorylation, which in turn aggravated EV71-induced neuroinflammation.

Targeting HDAC11 activity by FT895 restricts EV71 replication.

Enterovirus 71 (EV71) infection mainly causes hand, foot, and mouth disease (HFMD) and remains a serious public health problem to the children under the age of 5. Until now, there is no specific drug to treat HFMD in clinical and there is an urgent to explore the new target and the new drug to address clinical challenges. At present, we found histone deacetylase 11 (HDAC11) involves in supporting EV71 replication. We also used HDAC11 siRNA and an HDAC11 inhibitor FT895 to downregulate HDAC11 expression and found that targeting HDAC11 could significantly restrict EV71 replication in vitro and in vivo. Our results revealed the new role of HDAC11 participating in EV71 replication and broadened our knowledge regarding the functions of HDAC11 and the roles of HDACs in the epigenetic regulation of viral infectious diseases. Our results for the first time identified FT895 as an effective inhibitor of EV71 in vitro and in vivo, which may contribute to be a potential drug to treat HFMD.

Study on the Aging Mechanism and Microstructure Analysis of Rice-Husk-Ash- and Crumb-Rubber-Powder-Modified Asphalt.

In this paper, the rice husk ash and crumb rubber powder were used as a combined modifier for asphalt. The impact of the aging on the physical and rheological properties of crumb rubber powder, rice husk ash, and the combined modified asphalt was studied through the rolling thin film oven (RTFO) simulations. A Fourier-transform infrared Spectroscopy (FTIR) test was used to study the aging mechanisms of the combined crumb-rubber-powder- and rice-husk-ash-modified asphalt before and after aging through the changes in functional groups. Impacts of the combined, crumb rubber powder, and rice husk ash modifiers on the anti-aging characteristic of the asphalt binder were analyzed through different aging indices and the variations in intensity of the absorption peaks. According to the combined results, the addition of the combined crumb rubber powder, and rice husk ash could enhance the thermal oxidative aging resistance binder. Moreover, the optimal content of composite modified asphalt was (7% rice husk ash + 10% crumb rubber powder). In addition, the combined modified asphalt binder had all the peaks of neat asphalt, rice-husk-ash-modified asphalt, and crumb-rubber-powder-modified asphalt and no appearance of new peaks. A scanning electron microscope (SEM) test was carried out to observe the microstructure of the combined crumb-rubber-powder- and rice-husk-ash-modified asphalt binders. The obtained result demonstrated that different SEM images showed that the combined crumb rubber powder, and rice husk ash modifiers were uniformly dispersed inside the asphalt binder and consequently leading to format a homogeneous blended binder.

Outbreak of neuropathogenic equid herpesvirus 1 causing abortions in Yili horses of Zhaosu, North Xinjiang, China.

BACKGROUND: EHV-1 is one of the most serious viral pathogens that frequently cause abortion in horses around the world. However, so far, relatively little information is available on EHV-1 infections as they occur in China. In January 2021, during an abortion storm which occurred in Yili horses at the Chinese State Studs of Zhaosu (North Xinjiang, China), 43 out of 800 pregnant mares aborted. RESULTS: PCR detection revealed the presence of EHV-1 in all samples as the possible cause of all abortions, although EHV-4, EHV-2 and EHV-5 were also found to circulate in the aborted fetuses. Furthermore, the partial ORF33 sequences of the 43 EHV-1 shared 99.3-100% and 99.0-100% similarity in nucleotide and amino acid sequences respectively. These sequences not only indicated a highly conserved region but also allowed the strains to group into six clusters. In addition, based on the predicted ORF30 nucleotide sequence, it was found that all the strains carried a guanine at the 2254 nucleotide position (aspartic acid at position 752 of the viral DNA polymerase) and were, therefore, identified as neuropathogenic strains. CONCLUSION: This study is the first one that establishes EHV-1 as the cause of abortions in Yili horses, of China. Further characterization of the ORF30 sequences revealed that all the EHV-1 strains from the study carried the neuropathogenic genotype. Totally, neuropathogenic EHV-1 infection in China's horse population should be concerned although the virus only detected in Yili horse abortions.

Compression Helps Deep Learning in Image Classification.

The impact of JPEG compression on deep learning (DL) in image classification is revisited. Given an underlying deep neural network (DNN) pre-trained with pristine ImageNet images, it is demonstrated that, if, for any original image, one can select, among its many JPEG compressed versions including its original version, a suitable version as an input to the underlying DNN, then the classification accuracy of the underlying DNN can be improved significantly while the size in bits of the selected input is, on average, reduced dramatically in comparison with the original image. This is in contrast to the conventional understanding that JPEG compression generally degrades the classification accuracy of DL. Specifically, for each original image, consider its 10 JPEG compressed versions with their quality factor (QF) values from {100,90,80,70,60,50,40,30,20,10}. Under the assumption that the ground truth label of the original image is known at the time of selecting an input, but unknown to the underlying DNN, we present a selector called Highest Rank Selector (HRS). It is shown that HRS is optimal in the sense of achieving the highest Top k accuracy on any set of images for any k among all possible selectors. When the underlying DNN is Inception V3 or ResNet-50 V2, HRS improves, on average, the Top 1 classification accuracy and Top 5 classification accuracy on the whole ImageNet validation dataset by 5.6% and 1.9%, respectively, while reducing the input size in bits dramatically-the compression ratio (CR) between the size of the original images and the size of the selected input images by HRS is 8 for the whole ImageNet validation dataset. When the ground truth label of the original image is unknown at the time of selection, we further propose a new convolutional neural network (CNN) topology which is based on the underlying DNN and takes the original image and its 10 JPEG compressed versions as 11 parallel inputs. It is demonstrated that the proposed new CNN topology, even when partially trained, can consistently improve the Top 1 accuracy of Inception V3 and ResNet-50 V2 by approximately 0.4% and the Top 5 accuracy of Inception V3 and ResNet-50 V2 by 0.32% and 0.2%, respectively. Other selectors without the knowledge of the ground truth label of the original image are also presented. They maintain the Top 1 accuracy, the Top 5 accuracy, or the Top 1 and Top 5 accuracy of the underlying DNN, while achieving CRs of 8.8, 3.3, and 3.1, respectively.

NSC23766 and Ehop016 Suppress Herpes Simplex Virus-1 Replication by Inhibiting Rac1 Activity.

Herpes simplex virus-1 (HSV-1) infection of the eyes leads to herpes simplex virus keratitis (HSK), the main cause of infectious blindness in the world. As the current therapeutics for HSV-1 infection are rather limited and prolonged use of acyclovir (ACV)/ganciclovir (GCV) and in immunocompromised patients lead to the rise of drug resistant mutants, it underlines the urgent need for new antiviral agents with distinct mechanisms. Our study attempted to establish ras-related C3 botulinum toxin substrate 1 (Rac1) as a new therapeutic target for HSV-1 infection by using Rac1-specific inhibitors to evaluate the in vitro inhibition of virus growth. Our results showed that increased Rac1 activity facilitated HSV-1 replication and inhibition of Rac1 activity by NSC23766 and Ehop016 significantly reduced HSV-1 replication. Thus, we identified NSC23766 and Ehop016 as possessing potent anti-HSV-1 activities by suppressing the Rac1 activity, suggesting that Rac1 is a potential target for treating HSV-1-related diseases.

Enterovirus 71 infection induced Aquaporin-4 depolarization by increasing matrix metalloproteinase-9 activity.

Aquaporin-4 (AQP4) is the key water channel protein that regulates brain water homeostasis. Polarized expression of AQP4 on the astroglial endfeet facilitates its role in bi-directional brain water flux control. In the current study, we found that enterovirus 71 (EV71) infection induced depolarization of AQP4 in mouse brain, and demonstrated that ß-dystroglycan (ß-DG), the key component of dystrophin glycoprotein complex (DGC) that anchors AQP4 to the astroglial endfeet, was degraded upon infection. Elevated activity or expression of matrix metalloproteinase 9 (MMP9) upon infection was found in both mouse brains and patient cerebrospinal fluid (CSF) samples. Inhibiting MMP9 activity by SB-3CT rescued the decay of ß-DG and reduced the depolarization of AQP4. Brain edema induced by viral infection was also ameliorated by SB-3CT treatment in mice.

Non-tuberculous Mycobacterial Infection of the Musculoskeletal System Detected at Two Tertiary Medical Centres in Henan, China, 2016-2020.

Non-tuberculous mycobacterial (NTM) infection of the musculoskeletal system is rare but poses a grave threat to public health. These infections yield non-specific symptoms that remain undetected until the development of the later stages of the disease. In this study, we performed a retrospective review of 25 cases of musculoskeletal NTM infection at two tertiary medical centres over a 5-year period to determine the clinical features and improve the current clinical diagnosis and treatment. The most common mycobacterial species detected were Mycobacterium fortuitum in eleven patients, Mycobacterium abscessus in eight patients, Mycobacterium houstonense in three patients, Mycobacterium avium in two patients, and Mycobacterium smegmatis in one patient. The sites of infection included the limbs and joints, most commonly the knee (ten patients) and foot (six patients). The median duration from the onset of symptoms to diagnosis was 2.5 months (0.8-13.5 months). Deep sinus tracts extending to the surgical site were observed in 60% of the patients (15/25), and granulomatous inflammation and granulomatous inflammation with necrosis occurred in 60% of the patients (15/25). All patients underwent surgical treatment for infection control, and all patients, except one, received antimycobacterial therapy based on drug sensitivity assays. The median duration of the antimicrobial chemotherapy was 5 months (range: 3-20 months). At the final follow-up, 24 patients presented with absence of recurrence and one patient succumbed owing to heart failure after debridement. Our findings highlight the importance of vigilance and improvements in the diagnostic methods for musculoskeletal NTM infection. Aggressive surgical treatment and antimycobacterial drug treatment can help achieve satisfactory results.

Enterovirus 2C Protein Suppresses IKKα Phosphorylation by Recruiting IKKß and IKKα into Viral Inclusion Bodies.

The nuclear factor-kappa B (NF-κB) signaling network constitutes a first line of defense against the invading viruses. However, viruses also adopted multiple strategies to interfere with NF-κB activation. Enterovirus 71 (EV71), in the family Picornaviridae, has become the main pathogen responsible for hand, foot, and mouth disease. Recent studies have reported that the nonstructural protein 2C of EV71 inhibits TNF-α induced NF-κB activation by suppressing IKKß phosphorylation. In our study, we found that 2C can form inclusion bodies (IBs) in infected and transfected cells. Furthermore, 2C was able to sequester IKKß into IBs through direct interaction with IKKß. Although 2C did not directly interact with IKKα, viral protein 2C was able to sequester the IKKα into the IBs mediated by IKKß. Our in vitro data further demonstrated that EV71 2C could suppress IKKα phosphorylation. These all together support a novel mechanism for EV71 to escape from NF-κB response, in which the phosphorylation of IKKα was suppressed by being recruited into viral IBs in the presence of 2C and IKKß.

Rate Distortion Optimization: A Joint Framework and Algorithms for Random Access Hierarchical Video Coding.

This paper revisits the problem of rate distortion optimization (RDO) with focus on inter-picture dependence. A joint RDO framework which incorporates the Lagrange multiplier as one of parameters to be optimized is proposed. Simplification strategies are demonstrated for practical applications. To make the problem tractable, we consider an approach where prediction residuals of pictures in a video sequence are assumed to be emitted from a finite set of sources. Consequently the RDO problem is formulated as finding optimal coding parameters for a finite number of sources, regardless of the length of the video sequence. Specifically, in cases where a hierarchical prediction structure is used, prediction residuals of pictures at the same prediction layer are assumed to be emitted from a common source. Following this approach, we propose an iterative algorithm to alternatively optimize the selections of quantization parameters (QPs) and the corresponding Lagrange multipliers. Based on the results of the iterative algorithm, we further propose two practical algorithms to compute QPs and the Lagrange multipliers for the RA(random access) hierarchical video coding: the first practical algorithm uses a fixed formula to compute QPs and the Lagrange multipliers, and the second practical algorithm adaptively adjusts both QPs and the Lagrange multipliers. Experimental results show that these three algorithms, integrated into the HM 16.20 reference software of HEVC, can achieve considerable RD improvements over the standard HM 16.20 encoder, in the common RA test configuration.

Altered myelination in the Niemann-Pick type C1 mutant mouse.

Niemann-Pick type C1 (NPC1) disease is a lysosomal storage disorder caused by mutation of Npc1 or Npc2 gene, resulting in various progressive pathological features. Myelin defection is a major pathological problem in Npc1 mutant mice; however, impairment of myelin proteins in the developing brain is still incompletely understood. In this study, we showed that the expression of myelin genes and proteins is strongly inhibited from postnatal day 35 onwards including reduced myelin basic protein (MBP) expression in the brain. Furthermore, myelination characterized by MBP immunohistochemistry was strongly perturbed in the forebrain, moderately in the midbrain and cerebellum, and slightly in the hindbrain. Our results demonstrate that mutation of the Npc1 gene is sufficient to cause severe and progressive defects in myelination in the mouse brain.

[Activity of glial cells in the olfactory bulb of Niemann-Pick disease type C1 mice].

To study the pathological mechanisms of Niemann-Pick disease type C1, we observed the changes of activation of glial cells in the olfactory bulb of Npc1 mutant (Npc1(-/-)) mice. The genomic DNA was extracted from mouse tails for genotyping by PCR. Immunofluorescent histochemistry was performed to examine the activation of microglia and astrocytes in the olfactory bulb of Npc1(-/-) mice on postnatal day 30. NeuN, phosphorylated neurofilament (NF), Doublecortin (DCX), CD68 and GFAP were detected by Western blot. The results showed that Npc1 gene mutation strongly increased the activation of astrocytes and microglia in olfactory bulb associated with increased protein levels of CD68 and GFAP. Furthermore, the expression of phosphorylated NF was also significantly increased in the olfactory bulb of Npc1(-/-) mice compared with that in Npc1(+/+) mice. However, DCX expression was significantly reduced. The above results suggest that there are some early changes in the olfactory bulb of Npc1(-/-) mice.

An efficient DCT-based image compression system based on laplacian transparent composite model.

Recently, a new probability model dubbed the Laplacian transparent composite model (LPTCM) was developed for DCT coefficients, which could identify outlier coefficients in addition to providing superior modeling accuracy. In this paper, we aim at exploring its applications to image compression. To this end, we propose an efficient nonpredictive image compression system, where quantization (including both hard-decision quantization (HDQ) and soft-decision quantization (SDQ)) and entropy coding are completely redesigned based on the LPTCM. When tested over standard test images, the proposed system achieves overall coding results that are among the best and similar to those of H.264 or HEVC intra (predictive) coding, in terms of rate versus visual quality. On the other hand, in terms of rate versus objective quality, it significantly outperforms baseline JPEG by more than 4.3 dB in PSNR on average, with a moderate increase on complexity, and ECEB, the state-of-the-art nonpredictive image coding, by 0.75 dB when SDQ is OFF (i.e., HDQ case), with the same level of computational complexity, and by 1 dB when SDQ is ON, at the cost of slight increase in complexity. In comparison with H.264 intracoding, our system provides an overall 0.4-dB gain or so, with dramatically reduced computational complexity; in comparison with HEVC intracoding, it offers comparable coding performance in the high-rate region or for complicated images, but with only less than 5% of the HEVC intracoding complexity. In addition, our proposed system also offers multiresolution capability, which, together with its comparatively high coding efficiency and low complexity, makes it a good alternative for real-time image processing applications.

Quantization table design revisited for image/video coding.

Quantization table design is revisited for image/video coding where soft decision quantization (SDQ) is considered. Unlike conventional approaches, where quantization table design is bundled with a specific encoding method, we assume optimal SDQ encoding and design a quantization table for the purpose of reconstruction. Under this assumption, we model transform coefficients across different frequencies as independently distributed random sources and apply the Shannon lower bound to approximate the rate distortion function of each source. We then show that a quantization table can be optimized in a way that the resulting distortion complies with certain behavior. Guided by this new design principle, we propose an efficient statistical-model-based algorithm using the Laplacian model to design quantization tables for DCT-based image coding. When applied to standard JPEG encoding, it provides more than 1.5-dB performance gain in PSNR, with almost no extra burden on complexity. Compared with the state-of-the-art JPEG quantization table optimizer, the proposed algorithm offers an average 0.5-dB gain in PSNR with computational complexity reduced by a factor of more than 2000 when SDQ is OFF, and a 0.2-dB performance gain or more with 85% of the complexity reduced when SDQ is ON. Significant compression performance improvement is also seen when the algorithm is applied to other image coding systems proposed in the literature.

Transparent composite model for DCT coefficients: design and analysis.

The distributions of discrete cosine transform (DCT) coefficients of images are revisited on a per image base. To better handle, the heavy tail phenomenon commonly seen in the DCT coefficients, a new model dubbed a transparent composite model (TCM) is proposed and justified for both modeling accuracy and an additional data reduction capability. Given a sequence of the DCT coefficients, a TCM first separates the tail from the main body of the sequence. Then, a uniform distribution is used to model the DCT coefficients in the heavy tail, whereas a different parametric distribution is used to model data in the main body. The separate boundary and other parameters of the TCM can be estimated via maximum likelihood estimation. Efficient online algorithms are proposed for parameter estimation and their convergence is also proved. Experimental results based on Kullback-Leibler divergence and χ(2) test show that for real-valued continuous ac coefficients, the TCM based on truncated Laplacian offers the best tradeoff between modeling accuracy and complexity. For discrete or integer DCT coefficients, the discrete TCM based on truncated geometric distributions (GMTCM) models the ac coefficients more accurately than pure Laplacian models and generalized Gaussian models in majority cases while having simplicity and practicality similar to those of pure Laplacian models. In addition, it is demonstrated that the GMTCM also exhibits a good capability of data reduction or feature extraction-the DCT coefficients in the heavy tail identified by the GMTCM are truly outliers, and these outliers represent an outlier image revealing some unique global features of the image. Overall, the modeling performance and the data reduction feature of the GMTCM make it a desirable choice for modeling discrete or integer DCT coefficients in the real-world image or video applications, as summarized in a few of our further studies on quantization design, entropy coding design, and image understanding and management.

Joint optimization of run-length coding, Huffman coding, and quantization table with complete baseline JPEG decoder compatibility.

To maximize rate distortion performance while remaining faithful to the JPEG syntax, the joint optimization of the Huffman tables, quantization step sizes, and DCT indices of a JPEG encoder is investigated. Given Huffman tables and quantization step sizes, an efficient graph-based algorithm is first proposed to find the optimal DCT indices in the form of run-size pairs. Based on this graph-based algorithm, an iterative algorithm is then presented to jointly optimize run-length coding, Huffman coding, and quantization table selection. The proposed iterative algorithm not only results in a compressed bitstream completely compatible with existing JPEG and MPEG decoders, but is also computationally efficient. Furthermore, when tested over standard test images, it achieves the best JPEG compression results, to the extent that its own JPEG compression performance even exceeds the quoted PSNR results of some state-of-the-art wavelet-based image coders such as Shapiro's embedded zerotree wavelet algorithm at the common bit rates under comparison. Both the graph-based algorithm and the iterative algorithm can be applied to application areas such as web image acceleration, digital camera image compression, MPEG frame optimization, and transcoding, etc.

Down-sampling design in DCT domain with arbitrary ratio for image/video transcoding.

This paper proposes a designing framework for down-sampling compressed images/video with arbitrary ratio in the discrete cosine transform (DCT) domain. In this framework, we first derive a set of DCT-domain down-sampling methods which can be represented by a linear transform with double-sided matrix multiplication (LTDS) in the DCT domain and show that the set contains a wide range of methods with various complexity and visual quality. Then, for a preselected spatial-domain down-sampling method, we formulate an optimization problem for finding an LTDS to approximate the given spatial-domain down-sampling method for a trade-off between the visual quality and the complexity. By modeling LTDS as a multiple layer network, a so-called structural learning with forgetting algorithm is then applied to solve the optimization problem. The proposed framework has been applied to discover optimal LTDSs corresponding to a spatial down-sampling method with Butterworth low-pass filtering and bicubic interpolation. Experimental results show that the resulting LTDS achieves a significant reduction on the complexity when compared with other methods in the literature with similar visual quality.

Rate distortion optimization for H.264 interframe coding: a general framework and algorithms.

Rate distortion (RD) optimization for H.264 interframe coding with complete baseline decoding compatibility is investigated on a frame basis. Using soft decision quantization (SDQ) rather than the standard hard decision quantization, we first establish a general framework in which motion estimation, quantization, and entropy coding (in H.264) for the current frame can be jointly designed to minimize a true RD cost given previously coded reference frames. We then propose three RD optimization algorithms--a graph-based algorithm for near optimal SDQ in H.264 baseline encoding given motion estimation and quantization step sizes, an algorithm for near optimal residual coding in H.264 baseline encoding given motion estimation, and an iterative overall algorithm to optimize H.264 baseline encoding for each individual frame given previously coded reference frames-with them embedded in the indicated order. The graph-based algorithm for near optimal SDQ is the core; given motion estimation and quantization step sizes, it is guaranteed to perform optimal SDQ if the weak adjacent block dependency utilized in the context adaptive variable length coding of H.264 is ignored for optimization. The proposed algorithms have been implemented based on the reference encoder JM82 of H.264 with complete compatibility to the baseline profile. Experiments show that for a set of typical video testing sequences, the graph-based algorithm for near optimal SDQ, the algorithm for near optimal residual coding, and the overall algorithm achieve on average, 6%, 8%, and 12%, respectively, rate reduction at the same PSNR (ranging from 30 to 38 dB) when compared with the RD optimization method implemented in the H.264 reference software.

Quality-aware images.

We propose the concept of quality-aware image, in which certain extracted features of the original (high-quality) image are embedded into the image data as invisible hidden messages. When a distorted version of such an image is received, users can decode the hidden messages and use them to provide an objective measure of the quality of the distorted image. To demonstrate the idea, we build a practical quality-aware image encoding, decoding and quality analysis system, which employs: 1) a novel reduced-reference image quality assessment algorithm based on a statistical model of natural images and 2) a previously developed quantization watermarking-based data hiding technique in the wavelet transform domain.