scholarly journals REMOTE SENSING IMAGE QUALITY ASSESSMENT EXPERIMENT WITH POST-PROCESSING

2018 ◽  
Vol XLII-3 ◽  
pp. 665-668
Author(s):  
W. Jiang ◽  
S. Chen ◽  
X. Wang ◽  
Q. Huang ◽  
H. Shi ◽  
...  
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Quality Assessment ◽  
Physical Simulation ◽  
Image Quality Assessment ◽  
Imaging System ◽  
Post Processing ◽  
Improve Image Quality ◽  
System Parameters ◽  
Imaging Parameters

This paper briefly describes the post-processing influence assessment experiment, the experiment includes three steps: the physical simulation, image processing, and image quality assessment. The physical simulation models sampled imaging system in laboratory, the imaging system parameters are tested, the digital image serving as image processing input are produced by this imaging system with the same imaging system parameters. The gathered optical sampled images with the tested imaging parameters are processed by 3 digital image processes, including calibration pre-processing, lossy compression with different compression ratio and image post-processing with different core. Image quality assessment method used is just noticeable difference (JND) subject assessment based on ISO20462, through subject assessment of the gathered and processing images, the influence of different imaging parameters and post-processing to image quality can be found. The six JND subject assessment experimental data can be validated each other. Main conclusions include: image post-processing can improve image quality; image post-processing can improve image quality even with lossy compression, image quality with higher compression ratio improves less than lower ratio; with our image post-processing method, image quality is better, when camera MTF being within a small range.

A WAVELET-BASED IMAGE QUALITY ASSESSMENT METHOD

2008 ◽  
Vol 06 (04) ◽  
pp. 541-551 ◽  
Author(s):  
WEN LU ◽  
XINBO GAO ◽  
DACHENG TAO ◽  
XUELONG LI
Keyword(s):  
Image Processing ◽  
Computational Complexity ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Assessment Method ◽  
Reference Image ◽  
Subjective Perception ◽  
Good Accordance ◽  
Quality Assessment Method

Image quality is a key characteristic in image processing,10,11 image retrieval,12,13 and biometrics.14 In this paper, a novel reduced-reference image quality assessment method is proposed based on wavelet transform. By simulating the human visual system, we take the variance of the visual sensitive coefficients into account to measure a distorted image. The computational complexity of the proposed method is much lower compared with some existing methods. Experimental results demonstrate its advantages in terms of correlation coefficient, outlier ratio, transmitted information, and CPU cost. Moreover, it is also illustrated that the proposed method has a good accordance with human subjective perception.

scholarly journals ANALYSIS EXPOSURE INDEX AS AN OPTIMIZATION EFFORT ON EXAMINATION CHEST POSTERIOR ANTERIOR

2020 ◽  
Vol 4 (2) ◽  
pp. 50
Author(s):  
Muhammad Irsal ◽  
Firdha Adlia Syuhada ◽  
Yolanda Pangestu Ananda ◽  
Andre Galih Pratama Putra ◽  
Muhammad Rizky Syahputera ◽  
...  
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Imaging System ◽  
Radiographic Examination ◽  
Exposure Index ◽  
Post Processing ◽  
Improve Image Quality ◽  
Medical Physicists ◽  
Quantitative Descriptive ◽  
Posterior Anterior

Background: Radiographers are responsible for producing image quality which can provide accurate diagnostic information by considering the lowest possible radiation dose according to the As Low As Reasonably Achievable (ALARA) principle. Participation between radiographers and medical physicists is needed in optimizing efforts to control the selection of exposure factors by the required clinical radiographic examination. Purpose: To analyze the exposure index on examination chest posterior-anterior. Methods: Quantitative descriptive by analyzing the percentage of exposure index results used in chest PA radiographs as an effort to optimize: image quality and radiation dose indicators on chest PA examinations. Results: Optimization of exposure percentage results of 68%, 25% underexposure, 4% underexposure, 2% overexposure, 1% overexposure (noise). Radiographers have tried to optimize: image quality and image radiation dose by selecting exposure factors that are tailored to the patient’s condition and maximizing post-processing for increased quality. Conclusion: In optimizing the CR imaging system, it is necessary to understand exposure index, this is related to the underexposed, optimal, and overexposed categories, besides radiographers can take advantage of post-processing to improve image quality.

scholarly journals Deep Learning in Image Quality Assessment: Past, Present, and What Lies Ahead

2021 ◽  
Vol 2021 (1) ◽  
pp. 1-4
Author(s):  
Seyed Ali Amirshahi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Machine Learning Techniques ◽  
Short Paper ◽  
Subjective Quality Assessment ◽  
Learning Techniques ◽  
Objective Quality

Quality assessment of images plays an important role in different applications in image processing and computer vision. While subjective quality assessment of images is the most accurate approach due to issues objective quality metrics have been the go to approach. Until recently most such metrics have taken advantage of different handcrafted features. Similar (but with a slower speed) to other applications in image processing and computer vision, different machine learning techniques, more specifically Convolutional Neural Networks (CNNs) have been introduced in different tasks related to image quality assessment. In this short paper which is a supplement to a focal talk given with the same title at the London Imaging Meeting (LIM) 2021 we aim to provide a short timeline on how CNNs have been used in the field of image quality assessment so far, how the field could take advantage of CNNs to evaluate the image quality, and what we expect will happen in the near future.

A Novel Method of Image Quality Assessment

2014 ◽  
Vol 556-562 ◽  
pp. 5064-5067 ◽  
Author(s):  
Ming Wei Guo ◽  
Chen Bin Zhang ◽  
Zong Hai Chen
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Selective Attention ◽  
Visual System ◽  
Quality Assessment ◽  
Human Visual System ◽  
Image Quality Assessment ◽  
Visual Selective Attention ◽  
Research Areas ◽  
Novel Method

Image quality assessment (IQA) is one of the hot research areas in the field of image processing. For the reason that human being is the final receiver of the image, the image quality assessment should match the characteristics of human visual system. In this paper, we propose a novel method of image quality assessment which uses the visual selective attention of human visual system. For an image of a certain category, our method firstly detects the object in it and then calculate the saliency of the object. Lastly we use the combination of the detector’s score and the saliency as the image quality assessment. Experiments on some images of Pascal VOC dataset and INRIA dataset show that our method does well in image quality assessment.

Future Directions in Image Quality

2019 ◽  
Vol 2019 (1) ◽  
pp. 399-403
Author(s):  
Seyed Ali Amirshahi ◽  
Marius Pedersen
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Short Paper ◽  
Future Directions ◽  
Perceptual Judgement ◽  
Made In

With the advancements made in the field of image processing and computer vision, the last few decades have seen an increase in studies focused on image quality assessment. While this has resulted in the introduction of different new metrics which some show high correlation with the perceptual judgement of the human observers there still exists a huge room for improvement. In this short paper which is prepared as a complement to the workshop on Future Directions in Image Quality at CIC 27 in Paris, France we aim to introduce future directions in the field and challenges facing ahead.

scholarly journals A narrative move towards the exploration of gauging of image quality

2019 ◽  
Vol 3 (3) ◽  
Author(s):  
Tamil Kodi ◽  
Siva Prasad ◽  
Venkateswara Kiran ◽  
Praveen Kumar
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
The One ◽  
The Individual

Image quality assessment (IQA) acting as a noteworthy part in a variety of image processing applications. Manipulative eminence of an image is essential predicament in image and record handling and a range of procedure have been anticipated for IQA.widespread psychological substantiation shows that humans favor to conduct evaluations qualitatively comparative than numerical. However most frequently used IQA metrics are not reliable fine with the individual judgments of image quality. For the majority of the applications, the perceptual momentous compute is the one which can routinely estimate the worth of images or videos involving reliable behavior. This article explains about the various methods and their behavior towards the assessment of image quality.

A Novel Hybrid Image Quality Assessment Algorithm

2011 ◽  
Vol 4 (4) ◽  
pp. 107-108
Author(s):  
Deepa Maria Thomas ◽  
◽  
S. John Livingston
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment
Sign in / Sign up

Export Citation Format

Share Document