A novel image quality index using Moran I statistics

Research on the Efficiency Measurement and Spatial Spillover Effect of China’s Regional E-Commerce Poverty Alleviation from the Perspective of Sustainable Development

The development of e-commerce plays a very important role in changing the production and operation mode, optimizing the allocation of market resources, promoting sustainable development, and ultimately achieving the goal of e-commerce poverty alleviation. Therefore, the efficiency of e-commerce poverty alleviation has become a focus of attention for both the government and academia. The authors of this paper selected the panel data of 30 provinces and cities in China from 2010 to 2021, in order to measure the poverty alleviation efficiency of e-commerce in each province and city. We used the Moran’s I index to measure its spatial correlation to verify the existence of its spatial effect; we then used the spatial Durbin model to analyze the spatial spillover effect in the efficiency of e-commerce poverty alleviation. The conclusions are as follows: First, there is a significant positive spatial correlation of the efficiency of e-commerce poverty alleviation among different regions in China. Moran’s I index exceeds 0.5, indicating that there is a significant spatial effect in the efficiency of e-commerce poverty alleviation, and the existence of its spatial effect is unavoidable in the empirical analysis. Secondly, from the perspective of the efficiency of e-commerce poverty alleviation in various regions of the country, the overall e-commerce poverty alleviation efficiency is not high, and there are large differences among regions. The regions in which efficiency is higher include Tianjin, Beijing, and Shanghai. Regionally, the highest are in the east and the lowest are in the west. Secondly, from the decomposition of spatial spillover effects, the direct effects of each influencing factor are all positive. Only the financial development environment is less significant, and the indirect effects indicate that only four indicators have significant spatial spillover effects, of which the most significant is industrial agglomeration. The level of industrial agglomeration is not significantly related to the level of human capital, and there is a negative correlation between it and the efficiency of e-commerce poverty alleviation. The authors studied the poverty alleviation efficiency and spatial spillover effect of China’s regional e-commerce from the perspective of sustainable development, which is beneficial to China’s regional poverty alleviation results, providing practical guidance and decision-making reference for implementing differentiated coping strategies in different regions. The research complements, improves, and expands the research content in this field.

Local Indicators of Spatial Autocorrelation (LISA): Application to Blind Noise-Based Perceptual Quality Metric Index for Magnetic Resonance Images

Noise-based quality evaluation of MRI images is highly desired in noise-dominant environments. Current noise-based MRI quality evaluation methods have drawbacks which limit their effective performance. Traditional full-reference methods such as SNR and most of the model-based techniques cannot provide perceptual quality metrics required for accurate diagnosis, treatment and monitoring of diseases. Although techniques based on the Moran coefficients are perceptual quality metrics, they are full-reference methods and will be ineffective in applications where the reference image is not available. Furthermore, the predicted quality scores are difficult to interpret because their quality indices are not standardized. In this paper, we propose a new no-reference perceptual quality evaluation method for grayscale images such as MRI images. Our approach is formulated to mimic how humans perceive an image. It transforms noise level into a standardized perceptual quality score. Global Moran statistics is combined with local indicators of spatial autocorrelation in the form of local Moran statistics. Quality score is predicted from perceptually weighted combination of clustered and random pixels. Performance evaluation, comparative performance evaluation and validation by human observers, shows that the proposed method will be a useful tool in the evaluation of retrospectively acquired MRI images and the evaluation of noise reduction algorithms.

Characterisation of heterogeneity and spatial autocorrelation in phase separating mixtures using Moran's I

In complex colloidal systems, particle-poor regions can develop within particle-rich phases during sedimentation or creaming. These particle-poor regions are overlooked by 1D profiles, which are typically used to assess particle distributions in a sample. Alternative methods to visualise and quantify these regions are required to better understand phase separation, which is the focus of this paper. Magnetic resonance imaging has been used to monitor the development of compositional heterogeneity in a vesicle-polymer mixture undergoing creaming. T₂ relaxation time maps were used to identify the distribution of vesicles, with vesicle-poor regions exhibiting higher T₂ relaxation times than regions richer in vesicles. Phase separated structures displayed a range of different morphologies and a variety of image analysis methods, including first-order statistics, Fourier transformation, grey level co-occurrence matrices and Moran's I spatial autocorrelation, were used to characterise these structures, and quantify their heterogeneity. Of the image analysis techniques used, Moran's I was found to be the most effective at quantifying the degree and morphology of phase separation, providing a robust, quantitative measure by which comparisons can be made between a diverse range of systems undergoing phase separation. The sensitivity of Moran's I can be enhanced by the choice of weight matrices used.

JPEG2000 still image coding quality

This work demonstrates the image qualities between two popular JPEG2000 programs. Two medical image compression algorithms are both coded using JPEG2000, but they are different regarding the interface, convenience, speed of computation, and their characteristic options influenced by the encoder, quantization, tiling, etc. The differences in image quality and compression ratio are also affected by the modality and compression algorithm implementation. Do they provide the same quality? The qualities of compressed medical images from two image compression programs named Apollo and JJ2000 were evaluated extensively using objective metrics. These algorithms were applied to three medical image modalities at various compression ratios ranging from 10:1 to 100:1. Following that, the quality of the reconstructed images was evaluated using five objective metrics. The Spearman rank correlation coefficients were measured under every metric in the two programs. We found that JJ2000 and Apollo exhibited indistinguishable image quality for all images evaluated using the above five metrics (r > 0.98, p < 0.001). It can be concluded that the image quality of the JJ2000 and Apollo algorithms is statistically equivalent for medical image compression.

Spatiotemporal bounded noises and transitions induced by them in solutions of the real Ginzburg-Landau model

In this work, we introduce two spatiotemporal colored bounded noises, based on the zero-dimensional Cai-Lin and Tsallis-Borland noises. Then we study and characterize the dependence of the defined stochastic processes on both a temporal correlation parameter τ and a spatial coupling parameter λ. In particular, we found that varying λ may induce a transition of the distribution of the noise from bimodality to unimodality. With the aim of investigating the role played by bounded noises in nonlinear dynamical systems, we analyze the behavior of the real Ginzburg-Landau time-varying model additively perturbed by such noises. The observed phase transition phenomenology is quite different from that observed when the perturbations are unbounded. In particular, we observed an inverse order-to-disorder transition and a reentrant transition, with dependence on the specific type of bounded noise.

A novel medical image quality index

A novel medical image quality index using grey relational coefficient calculation is proposed in this study. Three medical modalities, DR, CT and MRI, using 30 or 60 images with a total of 120 images used for experimentation. These images were first compressed at ten different compression ratios (10 ∼ 100) using a medical image compression algorithm named JJ2000. Following that, the quality of the reconstructed images was evaluated using the grey relational coefficient calculation. The results were shown consistent with popular objective quality metrics. The impact of different image aspects on four grey relational coefficient methods were further tested. The results showed that these grey relational coefficients have different slopes but very high consistency for various image areas. Nagai's grey relational coefficient was chosen in this study because of higher calculation speed and sensitivity. A comparison was also made between this method and other windows-based objective metrics for various window sizes. Studies found that the grey relational coefficient results are less sensitive to window size changes. The performance of this index is better than some windows-based objective metrics and can be used as an image quality index.

Real-time extended dynamic range imaging in shearography

Extended dynamic range (EDR) imaging is a postprocessing technique commonly associated with photography. Multiple images of a scene are recorded by the camera using different shutter settings and are merged into a single higher dynamic range image. Speckle interferometry and holography techniques require a well-modulated intensity signal to extract the phase information, and of these techniques shearography is most sensitive to different object surface reflectivities as it uses self-referencing from a sheared image. In this paper the authors demonstrate real-time EDR imaging in shearography and present experimental results from a difficult surface reflectivity sample: a wooden panel painting containing gold and dark earth color paint.

Quality of compressed medical images

Previous studies have shown that Joint Photographic Experts Group (JPEG) 2000 compression is better than JPEG at higher compression ratio levels. However, some findings revealed that this is not valid at lower levels. In this study, the qualities of compressed medical images in these ratio areas ( approximately 20), including computed radiography, computed tomography head and body, mammographic, and magnetic resonance T1 and T2 images, were estimated using both a pixel-based (peak signal to noise ratio) and two 8 x 8 window-based [Q index and Moran peak ratio (MPR)] metrics. To diminish the effects of blocking artifacts from JPEG, jump windows were used in both window-based metrics. Comparing the image quality indices between jump and sliding windows, the results showed that blocking artifacts were produced from JPEG compression, even at low compression ratios. However, even after the blocking artifacts were omitted in JPEG compressed images, JPEG2000 outperformed JPEG at low compression levels. We found in this study that the image contrast and the average gray level play important roles in image compression and quality evaluation. There were drawbacks in all metrics that we used. In the future, the image gray level and contrast effect should be considered in developing new objective metrics.

Towards a new tool for the evaluation of the quality of ultrasound compressed images

This paper presents a new tool for the evaluation of ultrasound image compression. The goal is to measure the image quality as easily as with a statistical criterion, and with the same reliability as the one provided by the medical assessment. An initial experiment is proposed to medical experts and represents our reference value for the comparison of evaluation criteria. Twenty-one statistical criteria are selected from the literature. A cumulative absolute similarity measure is defined as a distance between the criterion to evaluate and the reference value. A first fusion method based on a linear combination of criteria is proposed to improve the results obtained by each of them separately. The second proposed approach combines different statistical criteria and uses the medical assessment in a training phase with a support vector machine. Some experimental results are given and show the benefit of fusion.

A blurring index for medical images

This study was undertaken to investigate a useful image blurring index. This work is based on our previously developed method, the Moran peak ratio. Medical images are often deteriorated by noise or blurring. Image processing techniques are used to eliminate these two factors. The denoising process may improve image visibility with a trade-off of edge blurring and may introduce undesirable effects in an image. These effects also exist in images reconstructed using the lossy image compression technique. Blurring and degradation in image quality increases with an increase in the lossy image compression ratio. Objective image quality metrics [e.g., normalized mean square error (NMSE)] currently do not provide spatial information about image blurring. In this article, the Moran peak ratio is proposed for quantitative measurement of blurring in medical images. We show that the quantity of image blurring is dependent upon the ratio between the processed peak of Moran's Z histogram and the original image. The peak ratio of Moran's Z histogram can be used to quantify the degree of image blurring. This method produces better results than the standard gray level distribution deviation. The proposed method can also be used to discern blurriness in an image using different image compression algorithms.

Lossy JPEG compression: easy to compress, hard to compare

OBJECTIVES

To review the literature on lossy compression in dental radiography and to discuss the importance and suitability of the methodology used for evaluation of image compression.

METHODS

A search of Medline (from 1966 to October 2004) was undertaken with the search expression "(Radiography, dental) and compression". Inclusion criterion was that the reference should be evaluating the effect of lossy image compression on diagnostic accuracy. For all included studies, information in relation to mode of image acquisition, image content, image compression, image display, and method of image evaluation was extracted.

RESULTS

12 out of 32 papers were included in the review. The design of these 12 studies was found to vary considerably. Parameters used to express the degree of information loss (DIL) were either or both compression ratio (CR) and compression level (CL). The highest acceptable CR reported in the studies ranged from 3.6% to 15.4%. Furthermore, different CR values were proposed even for the same diagnostic task, for example, for caries diagnosis CR ranged from 6.2% to 11.1%.

CONCLUSION

Lossy image compression can be used in clinical radiology if it does not conflict with national law. However, the acceptable DIL is difficult to express and standardize. CR is probably not suitable to express DIL, because it is image content dependent. CL is also probably not suitable to express DIL because of the lack of compression software standardization.

Quality evaluation of ultrasound imaging in the carotid artery based on normalization and speckle reduction filtering

Image quality is important when evaluating ultrasound images of the carotid for the assessment of the degree of atherosclerotic disease, or when transferring images through a telemedicine channel, and/or in other image processing tasks. The objective of this study was to investigate the usefulness of image quality evaluation based on image quality metrics and visual perception, in ultrasound imaging of the carotid artery after normalization and speckle reduction filtering. Image quality was evaluated based on statistical and texture features, image quality evaluation metrics, and visual perception evaluation made by two experts. These were computed on 80 longitudinal ultrasound images of the carotid bifurcation recorded from two different ultrasound scanners, the HDI ATL-3000 and the HDI ATL-5000 scanner, before (NF) and after (DS) speckle reduction filtering, after normalization (N), and after normalization and speckle reduction filtering (NDS). The results of this study showed that: (1) the normalized speckle reduction, NDS, images were rated visually better on both scanners; (2) the NDS images showed better statistical and texture analysis results on both scanners; (3) better image quality evaluation results were obtained between the original (NF) and normalized (N) images, i.e. NF-N, for both scanners, followed by the NF-DS images for the ATL HDI-5000 scanner and the NF-DS on the HDI ATL-3000 scanner; (4) the ATL HDI-5000 scanner images have considerable higher entropy than the ATL HDI-3000 scanner and thus more information content. However, based on the visual evaluation by the two experts, both scanners were rated similarly. The above findings are also in agreement with the visual perception evaluation, carried out by the two vascular experts. The results of this study showed that ultrasound image normalization and speckle reduction filtering are important preprocessing steps favoring image quality, and should be further investigated.

An SVD-based grayscale image quality measure for local and global assessment

The important criteria used in subjective evaluation of distorted images include the amount of distortion, the type of distortion, and the distribution of error. An ideal image quality measure should, therefore, be able to mimic the human observer. We present a new grayscale image quality measure that can be used as a graphical or a scalar measure to predict the distortion introduced by a wide range of noise sources. Based on singular value decomposition, it reliably measures the distortion not only within a distortion type at different distortion levels, but also across different distortion types. The measure was applied to five test images (airplane, boat, goldhill, Lena, and peppers) using six types of distortion (JPEG, JPEG 2000, Gaussian blur, Gaussian noise, sharpening, and DC-shifting), each with five distortion levels. Its performance is compared with PSNR and two recent measures.

Comparative evaluation of despeckle filtering in ultrasound imaging of the carotid artery

It is well-known that speckle is a multiplicative noise that degrades the visual evaluation in ultrasound imaging. The recent advancements in ultrasound instrumentation and portable ultrasound devices necessitate the need of more robust despeckling techniques for enhanced ultrasound medical imaging for both routine clinical practice and teleconsultation. The objective of this work was to carry out a comparative evaluation of despeckle filtering based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts in the assessment of 440 (220 asymptomatic and 220 symptomatic) ultrasound images of the carotid artery bifurcation. In this paper a total of 10 despeckle filters were evaluated based on local statistics, median filtering, pixel homogeneity, geometric filtering, homomorphic filtering, anisotropic diffusion, nonlinear coherence diffusion, and wavelet filtering. The results of this study suggest that the first order statistics filter lsmv, gave the best performance, followed by the geometric filter gf4d, and the homogeneous mask area filter lsminsc. These filters improved the class separation between the asymptomatic and the symptomatic classes based on the statistics of the extracted texture features, gave only a marginal improvement in the classification success rate, and improved the visual assessment carried out by the two experts. More specifically, filters lsmv or gf4d can be used for despeckling asymptomatic images in which the expert is interested mainly in the plaque composition and texture analysis; and filters lsmv, gf4d, or lsminsc can be used for the despeckling of symptomatic images in which the expert is interested in identifying the degree of stenosis and the plaque borders. The proper selection of a despeckle filter is very important in the enhancement of ultrasonic imaging of the carotid artery. Further work is needed to evaluate at a larger scale and in clinical practice the performance of the proposed despeckle filters in the automated segmentation, texture analysis, and classification of carotid ultrasound imaging.

Protecting patient privacy against unauthorized release of medical images in a group communication environment

In this paper, we identify and study an important patient privacy protection problem related to medical images. Following Health Insurance Portability and Accountability Act (HIPAA) mandate on privacy protection of patients' medical records, efforts have been devoted to guaranteeing the confidentiality of data and medical images during storage and transmission via an untrustworthy channel. However, to our knowledge, there has not been any effort towards protecting against unauthorized release of images by an authorized recipient. In this paper, we study the problem of tracing illegally distributed medical images in a group communication environment and identify a set of design requirements that must be met. We propose a fingerprint model suitable for many-to-many multicast, that is computationally efficient and scalable in user storage and key update communication. Simulation results also show that our scheme is highly robust to typical medical image processing and collusion attacks, while yielding high quality watermarked images.

A statistical method for evaluation quality of medical images: a case study in bit discarding and image compression

Many studies have been performed on quality evaluation for subtle differences in medical images. However, only limited success has been achieved. In this paper, medical images were prior manipulated by denoising, lossy compression and filtering. The Moran statistics is then applied to extract spatial information of images and using Kolmogorov-Smirnov (KS) test to determine whether the manipulated and original images differ significantly. Results show that on average discarding 1-2 bits in T1 and CR images or 2-3 bits in T2 and body CT images are indistinguishable. This method is also applied to a reconstructed MR, body CT image and an electronic SMPTE (Society of Motion Picture and Television Engineer) phantom from lossy image compression software. Compression ratios of 16:1 for a MR image, 8-9:1 for a cropped body CT image, 7:1 and 5:1 for high- and low-resolution regions in electronic phantom is proved undifferentiated from original. The proposed method is useful for complementing the human visual system, to optimize the performance of image compression technique.