An Image Quality Assessment Algorithm Based on Dual-scale Edge Structure Similarity

2007 ◽  
Author(s):  
Bin Liao ◽  
Yan Chen
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Edge Structure ◽  
Structure Similarity ◽  
Dual Scale

Image Evaluation Based on Region of Interest

2013 ◽  
Vol 339 ◽  
pp. 253-258
Author(s):  
Jun Qing Liu ◽  
Lei Ma ◽  
Yan Xiang ◽  
San Li Yi ◽  
Hong Lei Chen ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Image Quality Assessment ◽  
Region Of Interest ◽  
Image Evaluation ◽  
Visual Evaluation ◽  
Edge Structure ◽  
Structure Similarity ◽  
Weighted Combination ◽  
Dual Scale

Image quality assessment has broad applications in many fields, how to assess the quality of the image is an attractive research topic. In this paper, a ROIMDE method is proposed based on region of interest (ROI) and dual-scale edge structure similarity (SSIM), the quality assessment of the image is a weighted combination of ROI and non-ROI, the dual-scale edge structure similarity is used in ROI, and the classical structure similarity is applied in non-ROI. Experimental results show that, considering the influence of ROI, our model is more consistent with human subjective visual evaluation.

scholarly journals Image Enhancement and Feature Extraction of Cytomegalovirus Image using Hierarchical Ranking Convolutional Neural Network (HR-CNN)

2019 ◽  
Vol 8 (12) ◽  
pp. 3816-3820
Keyword(s):  
Neural Network ◽  
Image Quality ◽  
Quality Assessment ◽  
Image Enhancement ◽  
Mean Square Error ◽  
Image Quality Assessment ◽  
Similarity Index ◽  
Mean Square ◽  
Structure Similarity Index ◽  
Structure Similarity

Human Cytomegalovirus is becoming a common issue around the globe , mainly it deals with the infection of the fetus in the womb. Digital image processing plays a vital role in various fields especially in the field of medicine to have a better quality of image of viruses in various forms. To have better clarity of images even in microscopic images there might be some flaws in detection of viruses because of the intensities which occur due to atmospheric lights, to overcome the flaws in microscopic images there comes a technique image enhancement to overcome noise in images especially distortion free images to be produced based on some image quality assessment and to reduce noise in an image without any loss of information. In this paper the proposed methodology called Hierarchical Ranking Convolution Neural Network is introduced based on Upward/Downward hierarchy and Forward/Backward Hierarchy to extract features and to provide intensified image of the virus. Image quality assessment is done with the parameters and evaluated using Mean Square Error, Peak signal to Noise Ratio, Root Mean Square Error, Structure Similarity Index, Mean Structure Similarity Index to prove the accuracy.

scholarly journals No-Reference JPEG Image Quality Assessment Using Haar Wavelet Decomposition

1970 ◽  
Vol 5 (2) ◽  
pp. 61-72
Author(s):  
Irwan Prasetya Gunawan ◽  
Antony Halim
Keyword(s):  
Image Quality ◽  
Edge Detection ◽  
Quality Assessment ◽  
Wavelet Decomposition ◽  
Image Quality Assessment ◽  
Haar Wavelet ◽  
Detection Algorithm ◽  
Reference Image ◽  
Edge Structure ◽  
Quality Metric

This paper presents a novel method of no-reference image quality assessment for JPEG encoded images by means of multiresolution analysis using Haar wavelet decomposition. The proposed method takes advantage of the fact that JPEG encoded images are usually contaminated with blockiness artifacts. Blockiness artifact is modeled as a particular edge structure that transforms into a different edge structure when edge detection algorithm is applied. Subsequently after edge detection is performed, a 3-level Haar Wavelet Transform (HWT) is employed to construct an edge map, from which some features are derived. These features give meaningful information for blockiness distortions identification and quality assessment. The proposed quality metric was tested against publicly available JPEG subset of LIVE Image Database, whilst the detection algorithm was evaluated subjectively in terms of how well the automatic detection agrees with human’s perceived view. The detection algorithms as well as the proposed JPEG quality metric demonstrate satisfying performances.

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
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