Browse
Submit Data
Databases
API
Help

Dataset Information

22 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Study of Subjective Data Integrity for Image Quality Data Sets with Consumer Camera Content.

ABSTRACT: We need data sets of images and subjective scores to develop robust no reference (or blind) visual quality metrics for consumer applications. These applications have many uncontrolled variables because the camera creates the original media and the impairment simultaneously. We do not fully understand how this impacts the integrity of our subjective data. We put forward two new data sets of images from consumer cameras. The first data set, CCRIQ2, uses a strict experiment design, more suitable for camera performance evaluation. The second data set, VIME1, uses a loose experiment design that resembles the behavior of consumer photographers. We gather subjective scores through a subjective experiment with 24 participants using the Absolute Category Rating method. We make these two new data sets available royalty-free on the Consumer Digital Video Library. We also present their integrity analysis (proposing one new approach) and explore the possibility of combining CCRIQ2 with its legacy counterpart. We conclude that the loose experiment design yields unreliable data, despite adhering to international recommendations. This suggests that the classical subjective study design may not be suitable for studies using consumer content. Finally, we show that Hoßfeld-Schatz-Egger α failed to detect important differences between the two data sets.

SUBMITTER: Nawala J

PROVIDER: S-EPMC8321034 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

A posteriori correction of camera characteristics from large image data sets.

Project description:Large datasets are emerging in many fields of image processing including: electron microscopy, light microscopy, medical X-ray imaging, astronomy, etc. Novel computer-controlled instrumentation facilitates the collection of very large datasets containing thousands of individual digital images. In single-particle cryogenic electron microscopy ("cryo-EM"), for example, large datasets are required for achieving quasi-atomic resolution structures of biological complexes. Based on the collected data alone, large datasets allow us to precisely determine the statistical properties of the imaging sensor on a pixel-by-pixel basis, independent of any "a priori" normalization routinely applied to the raw image data during collection ("flat field correction"). Our straightforward "a posteriori" correction yields clean linear images as can be verified by Fourier Ring Correlation (FRC), illustrating the statistical independence of the corrected images over all spatial frequencies. The image sensor characteristics can also be measured continuously and used for correcting upcoming images.

| S-EPMC4464200 | biostudies-literature

Image and diagnosis quality of X-ray image transmission via cell phone camera: a project study evaluating quality and reliability.

Project description:IntroductionDevelopments in telemedicine have not produced any relevant benefits for orthopedics and trauma surgery to date. For the present project study, several parameters were examined during assessment of x-ray images, which had been photographed and transmitted via cell phone.Materials and methodsA total of 100 x-ray images of various body regions were photographed with a Nokia cell phone and transmitted via email or MMS. Next, the transmitted photographs were reviewed on a laptop computer by five medical specialists and assessed regarding quality and diagnosis.ResultsDue to their poor quality, the transmitted MMS images could not be evaluated and this path of transmission was therefore excluded. Mean size of transmitted x-ray email images was 394 kB (range: 265-590 kB, SD ± 59), average transmission time was 3.29 min ± 8 (CI 95%: 1.7-4.9). Applying a score from 1-10 (very poor - excellent), mean image quality was 5.8. In 83.2 ± 4% (mean value ± SD) of cases (median 82; 80-89%), there was agreement between final diagnosis and assessment by the five medical experts who had received the images. However, there was a markedly low concurrence ratio in the thoracic area and in pediatric injuries.DiscussionWhile the rate of accurate diagnosis and indication for surgery was high with a concurrence ratio of 83%, considerable differences existed between the assessed regions, with lowest values for thoracic images. Teleradiology is a cost-effective, rapid method which can be applied wherever wireless cell phone reception is available. In our opinion, this method is in principle suitable for clinical use, enabling the physician on duty to agree on appropriate measures with colleagues located elsewhere via x-ray image transmission on a cell phone.

| S-EPMC3474770 | biostudies-literature

Image content influences men's semen quality.

Project description:There is increasing evidence from non-human animals that males adjust their ejaculate expenditure according to the risk of sperm competition. In this study we show that, after controlling for lifestyle factors known to influence semen quality, human males viewing images depicting sperm competition had a higher percentage of motile sperm in their ejaculates. Many lifestyle variables were confirmed to influence semen quality, including the recent suggestion that storage of mobile phones close to the testes can decrease semen quality.

| S-EPMC1617155 | biostudies-literature

Dataset of chlorophyll content estimation of Coffea Canephora using Red and Near-Infrared consumer-grade camera.

Project description:This dataset presents a series of broad Red and Near-Infrared (NIR) bands obtained from consumer-grade camera in estimating chlorophyll contents in Robusta coffee (Coffea Canephora) plants at the leaf level. A total of 600 leaves were measured using direct-leaf tools namely SPAD-502 chlorophyll meter, Spectrometer, and modified consumer-grade camera using a 665?nm long-pass external filter.

| S-EPMC6214832 | biostudies-other

Impact of image segmentation on high-content screening data quality for SK-BR-3 cells.

Project description:BackgroundHigh content screening (HCS) is a powerful method for the exploration of cellular signalling and morphology that is rapidly being adopted in cancer research. HCS uses automated microscopy to collect images of cultured cells. The images are subjected to segmentation algorithms to identify cellular structures and quantitate their morphology, for hundreds to millions of individual cells. However, image analysis may be imperfect, especially for "HCS-unfriendly" cell lines whose morphology is not well handled by current image segmentation algorithms. We asked if segmentation errors were common for a clinically relevant cell line, if such errors had measurable effects on the data, and if HCS data could be improved by automated identification of well-segmented cells.ResultsCases of poor cell body segmentation occurred frequently for the SK-BR-3 cell line. We trained classifiers to identify SK-BR-3 cells that were well segmented. On an independent test set created by human review of cell images, our optimal support-vector machine classifier identified well-segmented cells with 81% accuracy. The dose responses of morphological features were measurably different in well- and poorly-segmented populations. Elimination of the poorly-segmented cell population increased the purity of DNA content distributions, while appropriately retaining biological heterogeneity, and simultaneously increasing our ability to resolve specific morphological changes in perturbed cells.ConclusionImage segmentation has a measurable impact on HCS data. The application of a multivariate shape-based filter to identify well-segmented cells improved HCS data quality for an HCS-unfriendly cell line, and could be a valuable post-processing step for some HCS datasets.

| S-EPMC2080643 | biostudies-literature

Evaluating the role of content in subjective video quality assessment.

Project description:Video quality as perceived by human observers is the ground truth when Video Quality Assessment (VQA) is in question. It is dependent on many variables, one of them being the content of the video that is being evaluated. Despite the evidence that content has an impact on the quality score the sequence receives from human evaluators, currently available VQA databases mostly comprise of sequences which fail to take this into account. In this paper, we aim to identify and analyze differences between human cognitive, affective, and conative responses to a set of videos commonly used for VQA and a set of videos specifically chosen to include video content which might affect the judgment of evaluators when perceived video quality is in question. Our findings indicate that considerable differences exist between the two sets on selected factors, which leads us to conclude that videos starring a different type of content than the currently employed ones might be more appropriate for VQA.

| S-EPMC3913198 | biostudies-other

Strategies for MCR image analysis of large hyperspectral data-sets.

Project description:Polymer microarrays are a key enabling technology for high throughput materials discovery. In this study, multivariate image analysis, specifically multivariate curve resolution (MCR), is applied to the hyperspectral time of flight secondary ion mass spectroscopy (ToF-SIMS) data from eight individual microarray spots. Rather than analysing the data individually, the data-sets are collated and analysed as a single large data-set. Desktop computing is not a practical method for undertaking MCR analysis of such large data-sets due to the constraints of memory and computational overhead. Here, a distributed memory High-Performance Computing facility (HPC) is used. Similar to what is achieved using MCR analysis of individual samples, the results from this consolidated data-set allow clear identification of the substrate material; furthermore, specific chemistries common to different spots are also identified. The application of the HPC facility to the MCR analysis of ToF-SIMS hyperspectral data-sets demonstrates a potential methodology for the analysis of macro-scale data without compromising spatial resolution (data 'binning'). Copyright © 2012 John Wiley & Sons, Ltd.

| S-EPMC3579489 | biostudies-literature

The Fewer Reasons, the More You Like It! How Decision-Making Heuristics of Image Quality Estimation Exploit the Content of Subjective Experience.

Project description:Imaging science has approached subjective image quality (IQ) as a perceptual phenomenon, with an emphasis on thresholds of defects. The paradigmatic design of subjective IQ estimation, the two-alternative forced-choice (2AFC) method, however, requires viewers to make decisions. We investigated decision strategies in three experiments both by asking the research participants to give reasons for their decisions and by examining the decision times. We found that typical for larger quality differences is a smaller set of subjective attributes, resulting from convergent attention toward the most salient attribute, leading to faster decisions and better accuracy. Smaller differences are characterized by divergent attention toward different attributes and an emphasis on preferential attributes instead of defects. In larger differences, attributes have sigmoidal relationships between their visibility and their occurrence in explanations. For other attributes, this relationship is more random. We also examined decision times in different attribute configurations to clarify the heuristics of IQ estimation, and we distinguished a top-down-oriented Take-the-Best heuristic and a bottom-up visual salience-based heuristic. In all experiments, heuristic one-reason decision-making endured as a prevailing strategy independent of quality difference or task.

| S-EPMC9253696 | biostudies-literature

Databases for evaluating interferences between affective content and image quality.

Project description:The two databases here described were generated to evaluate the role of affective content while assessing image quality (Corchs et al., 2018) [1]. The databases are composed of images JPEG-compressed together with the subjective quality scores collected during psychophysical experiments. To reduce interferences in quality perception due to image semantic, we have restricted the semantic content, choosing only close-ups of face images, and we have considered only two emotion categories (happy and sad). We have selected 23 images with happy faces and 23 images with sad faces of high quality. For what concerns image quality we have considered JPEG-distortion with 4 levels of compression, corresponding to q-factors 10, 15, 20, 30. The first image database, hereafter called MMSP-FaceA, is thus composed of 230 images (23+23) × 5 quality levels (including the original high quality pristine images). To better consider only interferences in quality perception due to affective content, we have generated a second image database where the background of images belonging to MMSP-FaceA has been cut off. This second image database is labelled as MMSP-FaceB. Psychophysical experiments were conducted, on a controlled web-based interface, where participants rated the image quality of the two databases in a five point scale. The two final databases MMSP-FaceA and MMSP-FaceB are thus composed of 230 images each, together with the raw quality scores assigned by the observers, and are available at our laboratory web site: www.mmsp.unimib.it/download.

| S-EPMC6383121 | biostudies-literature

Iterative Reconstruction Improves Both Objective and Subjective Image Quality in Acute Stroke CTP.

Project description:PURPOSE:Computed tomography perfusion (CTP) imaging in acute ischemic stroke (AIS) suffers from measurement errors due to image noise. The purpose of this study was to investigate if iterative reconstruction (IR) algorithms can be used to improve the diagnostic value of standard-dose CTP in AIS. METHODS:Twenty-three patients with AIS underwent CTP with standardized protocol and dose. Raw data were reconstructed with filtered back projection (FBP) and IR with intensity levels 3, 4, 5. Image quality was objectively (quantitative perfusion values, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)) and subjectively (overall image quality) assessed. Ischemic core and perfusion mismatch were visually rated. Discriminative power for tissue outcome prediction was determined by the area under the receiver operating characteristic curve (AUC) resulting from the overlap between follow-up infarct lesions and stepwise thresholded CTP maps. RESULTS:With increasing levels of IR, objective image quality (SNR and CNR in white matter and gray matter, elimination of error voxels) and subjective image quality improved. Using IR, mean transit time (MTT) was higher in ischemic lesions, while there was no significant change of cerebral blood volume (CBV) and cerebral blood flow (CBF). Visual assessments of perfusion mismatch changed in 4 patients, while the ischemic core remained constant in all cases. Discriminative power for infarct prediction as represented by AUC was not significantly changed in CBV, but increased in CBF and MTT (mean (95% CI)): 0.72 (0.67-0.76) vs. 0.74 (0.70-0.78) and 0.65 (0.62-0.67) vs 0.67 (0.64-0.70). CONCLUSION:In acute stroke patients, IR improves objective and subjective image quality when applied to standard-dose CTP. This adds to the overall confidence of CTP in acute stroke triage.

| S-EPMC4773110 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data