A Comparative Analysis on Image Quality Assessment for Real Time Satellite Images
S. Rajkumar,G. Malathi +1 more
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TLDR
The characteristics of different quality metrics are concluded and further the quality metric appropriate to various distortions are identified and the proposed quality metric is successfully identified.Abstract:
Objectives: The objective of this paper is to analyze the different image quality metrics by testing and comparing with different distorted set of satellite images. Methods/Statistical Analysis: In this paper, we propose the methods for analyzing the quality of real time images that are corrupted due to different distortions. The several quality metrics are applied and ultimately the best metrics are derived based on the type of degradation. Different metrics such as metric based on single image and metric based on two images have been tested with different real time satellite images from NASA data sets. Findings: This framework will help to identify the metrics in order to prove the proposed filtering schemes that are applied to the corrupted images. Based on the results, we have concluded the characteristics of different quality metrics and further we successfully identified the quality metric appropriate to various distortions. Application/Improvements: The proposed quality metric analysis is used to estimate the performance of any filtering schemes which are used to enhance the quality of any real time images such as remote sensing field.read more
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References
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Image quality assessment: from error visibility to structural similarity
TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.
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A universal image quality index
Zhou Wang,Alan C. Bovik +1 more
TL;DR: Although the new index is mathematically defined and no human visual system model is explicitly employed, experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error.
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Blind image quality assessment using joint statistics of gradient magnitude and Laplacian features.
TL;DR: This work proposes a novel BIQA model that utilizes the joint statistics of two types of commonly used local contrast features: 1) the gradient magnitude (GM) map and 2) the Laplacian of Gaussian response.
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Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition
TL;DR: A novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts and the experimental results show that the proposed method is highly competitive compared with other state-of-the-art approaches.