A full reference image quality assessment method for retina-like sensor

2013 ◽  
Author(s):  
Zhihu Luo ◽  
Fengmei Cao
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Assessment Method ◽  
Reference Image ◽  
Full Reference ◽  
Quality Assessment Method

Image quality assessment method based on relation intensity and details similarity

2018 ◽  
Vol 32 (34n36) ◽  
pp. 1840085
Author(s):  
Ruxi Xiang ◽  
Feng Wu
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Intensity Ratio ◽  
Image Quality Assessment ◽  
Assessment Method ◽  
Reference Image ◽  
Full Reference ◽  
Quality Assessment Method ◽  
Pooling Strategy ◽  
The Mean

In this paper, we present an effective quality assessment method based on the relation intensity ratio and detail similarity for image quality assessment (IQA) with the full reference image, which first allows us to compute the nonlinear gradient magnitude with Gaussian smoothing of the reference and distorted images and construct the relation intensity ratio and detail similarity between them. Next, the final IQA map is formed by linearly combining the relation intensity ratio with the detail similarity. Finally, we adopt a new pooling strategy which effectively integrates the mean and standard deviation of the final IQA map to accurately predict image quality. Experiments based on two publicly available databases show that the proposed method can provide accurate predictions compared with most state-of-the-art IQA methods.

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.

PENILAIAN KUALITI IMEJ DIGITAL BERDASARKAN KAEDAH CIRI-CIRI SISTEM PENGLIHATAN MANUSIA DAN PRINSIP STRUKTUR IMEJ

2016 ◽  
Vol 78 (5-10) ◽  
Author(s):  
Bahbibi Rahmatullah ◽  
Siti Tasnim Mahamud
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Visual Information ◽  
Image Quality Assessment ◽  
Digital Images ◽  
Reference Method ◽  
Assessment Method ◽  
Reference Image ◽  
Human Observer ◽  
Full Reference

Tremendous advances of information technology provide a large role for digital images for delivering information quickly and accurately. However, digital images are exposed to distortions and imperfect quality during acquisition, compression, transmission, processing and reproduction. Therefore, the development of effectively image quality assessment (IQA) is crucial in order to identify and measure the distortion in image quality. Perception by human observers (manually) as the ultimate receiver of the visual information contained in an image and most reliable to assess the quality of image. However, manual subjective assessment method is considered costly and time consuming. This lead to the development of proposed automatic method to measure image quality as accurately as the manual method. The goal of objective image quality assessment is to develop a computational model that can accurately and automatically predict the perceptual image quality. An ideal objective IQA method should be able to imitate the quality predictions of an average human observer. Full-reference image quality assessment is a method where image with perfect quality provided as a reference image for guiding the IQA system. This paper presents the study and comparison between two full-reference method that frequently used in IQA system that is method based on the properties of human visual system (HVS) and method based on principle of image structure. Both of this method is proven can be used to measure digital images quality accurately and depends on distortion types that occurred on measured images.

A New Image Quality Assessment Method Based on SSIM and TV Model

2011 ◽  
Vol 65 ◽  
pp. 542-550
Author(s):  
Lu Lu Pang ◽  
Cong Li Li ◽  
De Ning Qi ◽  
Tao Zou
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Explicit Knowledge ◽  
Image Quality Assessment ◽  
Structural Similarity ◽  
Assessment Method ◽  
Reference Image ◽  
Distorted Image ◽  
Quality Assessment Method ◽  
Reference Images

In this paper, a new image quality assessment method has been proposed in which can judge the quality of images without explicit knowledge of the reference images ,it is based on the SSIM(Structural Similarity) and TV(total variation) model. Firstly, add noises to distorted image to quantitatively determine, it can get the degraded image; secondly, use the improved self-adaptive gradient weights of the TV algorithms to denoising the distorted image, it can get the “fake” reference image, then use the classical SSIM methods to make reference evaluation between the distorted image and the “fake” reference image, after modified, the results is the no reference evaluating indicator. The experiment separated use the standard testing images and the degraded images from the LIVE database to make evaluate experiment, the result show that it is consistent to the result of MOS. This method is no need of reference images, it can use widely.

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