摘要 :
While recently a few image fusion quality measures have been proposed, analytical studies of these measures have been lacking. Here, we focus on one popular mutual information-based quality measure and weighted averaging image fus...
展开
While recently a few image fusion quality measures have been proposed, analytical studies of these measures have been lacking. Here, we focus on one popular mutual information-based quality measure and weighted averaging image fusion. Based on an image formation model, we obtain a closed-form expression for the quality measure and mathematically analyze its properties under different types of image distortion. Tests with real images are also presented which agree with the conclusions of the analytical results. The results show the quality measure studied does not generally properly characterize increases in the distortion (noise and blurring) of the images which are input into a weighted averaging fusion algorithm.
收起
摘要 :
In this paper the problem of quality assessment of images containing various types of distortions is concerned. Many image quality metrics proposed during last decade are quite well correlated with human perception of various kind...
展开
In this paper the problem of quality assessment of images containing various types of distortions is concerned. Many image quality metrics proposed during last decade are quite well correlated with human perception of various kinds of distortions with the assumption that only a single type of distortions is present in the image. One of the main reasons of such approach is the lack of datasets containing subjective quality assessment results of multiply distorted images. However, after the development of LIVE Multiply Distorted Image Quality Database, a new challenge related to verification of usability of known metrics as well as the development of new ones has appeared. In this paper, the results of such verification is presented not only for some well-known metrics but also for recently proposed combined metrics together with the proposed new combined metrics optimized for multiply distorted images. The new metrics outperform previously proposed ones in the aspect of linear correlation with subjective evaluations of images containing multiple distortions.
收起
摘要 :
Evaluation of noise content or distortions present in an image is same as assessing the quality of an image. Measurement of such quality index is challenging in the absence of reference image. In this paper, a survey of existing a...
展开
Evaluation of noise content or distortions present in an image is same as assessing the quality of an image. Measurement of such quality index is challenging in the absence of reference image. In this paper, a survey of existing algorithms for no-reference image quality assessment is presented. This survey includes type of noise and distortions covered, techniques and parameters used by these algorithms, databases on which the algorithms are validated and benchmarking of their performance with each other and also with human visual system. (C) 2015 Elsevier GmbH. All rights reserved.
收起
摘要 :
Image quality assessment (IQA) is one of the constantly active areas of research in computer vision. Starting from the idea of Universal Image Quality Index (UIQI), followed by well-known Structural Similarity (SSIM) and its numer...
展开
Image quality assessment (IQA) is one of the constantly active areas of research in computer vision. Starting from the idea of Universal Image Quality Index (UIQI), followed by well-known Structural Similarity (SSIM) and its numerous extensions and modifications, through Feature Similarity (FSIM) towards combined metrics using the multimetric fusion approach, the development of image quality assessment is still in progress. Nevertheless, regardless of new databases and the potential use of deep learning methods, some challenges remain still up to date. Some of the IQA metrics can also be used efficiently for alternative purposes, such as texture similarity estimation, quality evaluation of 3D images and 3D printed surfaces as well as video quality assessment.
收起
摘要 :
The use of mobile devices for medical image capture has become increasingly popular given the widespread use of smartphone cameras. Prior studies have generally compared mobile phone capture images to digitized images. However, ma...
展开
The use of mobile devices for medical image capture has become increasingly popular given the widespread use of smartphone cameras. Prior studies have generally compared mobile phone capture images to digitized images. However, many underserved and rural areas without picture archiving and communication systems (PACS) still depend greatly on the use of film radiographs. Additionally, there is a scarcity of specialty-trained or formally licensed radiologists in many of these regions. Subsequently, there is great potential for the use of smartphone capture of plain radiograph films which would allow for increased access to economical and efficient consultation from board-certified radiologists abroad. The present study addresses the ability to diagnose a subset of radiographic findings identified on both the original film radiograph and the captured camera phone image.
收起
摘要 :
The paper presents new methods tor estimating effective coverage of the image databases in spatial information (SI) vs. colorfulness (CF) spaee. Existing and commonly used metries are vulnerable to databases containing very differ...
展开
The paper presents new methods tor estimating effective coverage of the image databases in spatial information (SI) vs. colorfulness (CF) spaee. Existing and commonly used metries are vulnerable to databases containing very different images in terms of SI and CF, whieh can maximize the relative ranges, while preserving, in speeifre cases, high uniformity. The area covered by convex hull created on SI x CF spaee can be large, but the interior of the convex envelope might be poorly filled. To overcome this Haw, a fill factor is proposed, which determines how well the convex hull area is utilized. In the paper the method is described in details and presented on a few existing databases, as well as on artificial, non-existing databases to prove its robustness in different scenarios. Provided results show that new metric is closer to the actual coverage than existing methods.
收起
摘要 :
Introduction: Radiographers routinely undertake many initiatives to balance image quality with radiation dose (optimisation). For optimisation studies to be successful image quality needs to be carefully evaluated. Purpose was to ...
展开
Introduction: Radiographers routinely undertake many initiatives to balance image quality with radiation dose (optimisation). For optimisation studies to be successful image quality needs to be carefully evaluated. Purpose was to 1) discuss the strengths and limitations of a Visual Grading Analysis (VGA) method for image quality evaluation and 2) to outline the method from a radiographer's perspective. Methods: A possible method for investigating and discussing the relationship between radiographic image quality parameters and the interpretation and perception of X-ray images is the VGA method. VGA has a number of advantages such as being low cost and a detailed image quality assessment, although it is limited to ensure the images convey the relevant clinical information and relate the task based radiography. Results: Comparing the experience of using VGA and Receiver Operating Characteristic (ROC) it is obviously that less papers are published on VGA (Pubmed n=1.384) compared to ROC (Pubmed n=122.686). Hereby the scientific experience of the VGA method is limited compared to the use of ROC. VGA is, however, a much newer method and it is slowly gaining more and more attention. Conclusion: The success of VGA requires a number of steps to be completed, such as defining the VGA criteria, choosing the VGA method (absolute or relative), including observers, finding the best image display platforms, training observers and selecting the best statistical method for the study purpose should be thoroughly considered. Implication for practice: Detailed evaluation of image quality for optimisation studies related to technical definition of image quality.
收起
摘要 :
One of the most relevant issues in image processing and analysis is a reliable image quality assessment. During last several years numerous metrics have been proposed by various researchers which are much better than traditionally...
展开
One of the most relevant issues in image processing and analysis is a reliable image quality assessment. During last several years numerous metrics have been proposed by various researchers which are much better than traditionally used Mean Squared Error or similar metrics in the aspect of the accordance with human perception of various distortions. Nevertheless, the direct application of such metrics does not provide high correlation with subjective scores because of the required additional nonlinear mapping. Unfortunately, such fitting, typically applied for each image database using the logistic function, leads to different values of parameters for each dataset. As a more universal approach, some nonlinear combinations of various metrics have been proposed recently which do not require any nonlinear mapping. In the paper an extended combined similarity metric is proposed, which provides high prediction accuracy of the image quality with highly linear correlation with subjective scores. The results of extensive tests conducted using the most relevant image quality assessment databases are also presented.
收起
摘要 :
As all kinds of self-contained display products have become popular, various technologies for improving printing applications have gradually been ignored or even stagnated. However, the number of printed matters in life has not de...
展开
As all kinds of self-contained display products have become popular, various technologies for improving printing applications have gradually been ignored or even stagnated. However, the number of printed matters in life has not decreased. Every day our lives are full of various printed materials, such as newspapers, magazines, leaflets, product packaging, and so on. The waste and pollution caused by printing technology are usually recessive, and not everyone values it. Unfortunately, people often overlook the waste of resources and environmental pollution caused by the manufacturing process, ink, toner, and printers. The method proposed in this paper uses a color difference model to find a manner that is not easy to notice by the human eye to save ink. The proposed method considers feasibility and practicability, and users can quickly find suitable settings for their applications. Also, through the actual printed pictures, the experimental results show that only 67.57% of the original ink consumption is required to obtain an equivalent print quality that is difficult to perceive by the human eye. Our proposed method will benefit the printing industry and reduce ink consumption on consumer printers, contributing to cost control and being nature-friendly.
收起
摘要 :
Concerns about the reliability of expression data from microarrays inspire ongoing research into measurement error in these experiments. Error arises at both the technical level within the laboratory and the experimental level. In...
展开
Concerns about the reliability of expression data from microarrays inspire ongoing research into measurement error in these experiments. Error arises at both the technical level within the laboratory and the experimental level. In this paper, we will focus on estimating the spot-specific error, as there are few currently available models. This paper outlines two different approaches to quantify the reliability of spot-specific intensity estimates. In both cases, the spatial correlation between pixels and its impact on spot quality is accounted for. The first method is a straightforward parametric estimate of within-spot variance that assumes a Gaussian distribution and accounts for spatial correlation via an overdispersion factor. The second method employs a nonparametric quality estimate referred to throughout as the mean square prediction error (MSPE). The MSPE first smoothes a pixel region and then measures the difference between actual pixel values and the smoother. Both methods herein are compared for real and simulated data to assess numerical characteristics and the ability to describe poor spot quality. We conclude that both approaches capture noise in the microarray platform and highlight situations where one method or the other is superior.
收起
原文获取