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首页> 外文期刊>International journal of computational vision and robotics >Colour image quality assessment using Laplacian pyramid decomposition
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Colour image quality assessment using Laplacian pyramid decomposition

机译:使用拉普拉斯金字塔分解的彩色图像质量评估

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摘要

Today's world has witnessed tremendous increase in use of multimedia and internet. This demands an image quality metric capable of evaluating image quality, accurately and automatically. Natural scenes are of excellent quality and all natural scenes exhibit similar statistical properties. Natural scene statistics is successfully used in image quality assessment which is based on the hypothesis that introduction of distortion in an image causes deviation from statistical properties. Amount of deviation in the statistical property of an image is found to be proportional to the amount of distortion. A neural network-based image quality metric needs such natural scene statistical feature to predict the image quality blindly. This paper presents a new feature for colour image quality assessment that is extracted after decomposing given image into different frequency bands of hue plane. In future, this feature will be used in a classifier to evaluate colour image quality.
机译:当今世界见证了多媒体和互联网使用的巨大增长。这需要能够准确,自动地评估图像质量的图像质量度量。自然场景具有出色的质量,所有自然场景都表现出相似的统计属性。自然场景统计信息已成功用于图像质量评估,其基于以下假设:图像中引入失真会导致偏离统计属性。发现图像的统计特性中的偏差量与失真量成正比。基于神经网络的图像质量度量需要这种自然场景统计功能,才能盲目地预测图像质量。本文提出了一种彩色图像质量评估的新功能,该功能是在将给定图像分解为色调平面的不同频段后提取的。将来,此功能将在分类器中用于评估彩色图像质量。

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