公开(公告)号：US20160350941A1

公开(公告)日：2016-12-01

申请号：US15233950

申请日：2016-08-11

Applicant: Ningbo University

Inventor： Mei Yu ,  Zhaoyun Wang ,  Fen Chen ,  Meiling He

IPC: G06T7/40

CPC classification number: G06T7/0002 ,  G06K9/4661 ,  G06K9/6252 ,  G06T2207/10012 ,  G06T2207/20081 ,  G06T2207/30168 ,  H04N13/00 ,  H04N13/133

Abstract: An objective assessment method for a stereoscopic image quality combined with manifold characteristics and binocular characteristics trains a matrix after dimensionality reduction and whitening obtained from natural scene plane images through an orthogonal locality preserving projection algorithm, for obtaining a best mapping matrix. Image blocks, not important for visual perception, are removed. After finishing selecting the image blocks, through the best mapping matrix, manifold characteristic vectors of the image blocks are extracted, and a structural distortion of a distorted image is measured according to a manifold characteristic similarity. Considering influences of an image luminance variation on human eyes, a luminance distortion of the distorted image is calculated according to a mean value of the image blocks. After obtaining the manifold similarity and the luminance similarity, quality values of the left and right viewpoint images are processed with linear weighting to obtain a quality value of the distorted stereoscopic image.

Abstract translation: 对于与歧管特征和双目特征组合的立体图像质量的客观评估方法，通过正交局部保留投影算法从自然场景平面图像获得的维数降低和白化之后训练矩阵，以获得最佳映射矩阵。 图像块，对视觉感知不重要，被删除。 在完成选择图像块之后，通过最佳映射矩阵，提取图像块的多重特征向量，并根据流形特征相似度来测量失真图像的结构失真。 考虑到图像亮度变化对人眼的影响，根据图像块的平均值计算失真图像的亮度失真。 在获得歧管相似性和亮度相似性之后，利用线性加权处理左和右视点图像的质量值，以获得失真的立体图像的质量值。

公开(公告)号：US09892499B2

公开(公告)日：2018-02-13

申请号：US15233950

申请日：2016-08-11

Applicant: Ningbo University

Inventor： Mei Yu ,  Zhaoyun Wang ,  Fen Chen ,  Meiling He

IPC: G06K9/00 ,  G06T7/00 ,  H04N13/00 ,  G06K9/46 ,  G06K9/62

CPC classification number: G06T7/0002 ,  G06K9/4661 ,  G06K9/6252 ,  G06T2207/10012 ,  G06T2207/20081 ,  G06T2207/30168 ,  H04N13/00 ,  H04N13/133

Abstract: An objective assessment method for a stereoscopic image quality combined with manifold characteristics and binocular characteristics trains a matrix after dimensionality reduction and whitening obtained from natural scene plane images through an orthogonal locality preserving projection algorithm, for obtaining a best mapping matrix. Image blocks, not important for visual perception, are removed. After finishing selecting the image blocks, through the best mapping matrix, manifold characteristic vectors of the image blocks are extracted, and a structural distortion of a distorted image is measured according to a manifold characteristic similarity. Considering influences of an image luminance variation on human eyes, a luminance distortion of the distorted image is calculated according to a mean value of the image blocks. After obtaining the manifold similarity and the luminance similarity, quality values of the left and right viewpoint images are processed with linear weighting to obtain a quality value of the distorted stereoscopic image.

公开(公告)号：US20170177975A1

公开(公告)日：2017-06-22

申请号：US15062112

申请日：2016-03-06

Applicant: Ningbo University

Inventor： Mei Yu ,  Zhaoyun Wang ,  Zongju Peng ,  Fen Chen ,  Yang Song

IPC: G06K9/62 ,  G06K9/46 ,  G06K9/52 ,  G06T7/40

CPC classification number: G06K9/6256 ,  G06K9/036 ,  G06K9/4652 ,  G06K9/6248 ,  G06T7/90 ,  G06T2207/30168

Abstract: An image quality objective evaluation method based on manifold feature similarity is disclosed, which firstly adopts visual salience and visual threshold to remove image blocks which are unimportant to visual perception, namely, uses roughing selection and fine selection; and then utilizes the best mapping matrix after block selection to extract manifold feature vectors of image blocks which are selected from original undistorted natural scene images and distorted images to be evaluated; and then measures the structural distortion of distorted images according to manifold feature similarity; and then considers effects of image brightness changes on human eyes and obtains the brightness distortion of distorted images based on an average value of image blocks, and finally obtains quality scores according to structural distortion and brightness distortion; which allows the method of the present invention to have a higher evaluation accuracy, and also expands the evaluation capacity to various distortions.