Due to the rapid development of free-viewpoint television (FVT), Depth-Image-Based Rendering (DIBR) technology has been widely used to synthesize images of virtual view-points. However, the types of distortions in the synthesized images are different from those of natural images, such as discontinuity, flickering, stretching, etc. To measure the distortion occurred in the synthesized images, we propose a full-reference (FR) quality assessment method by local variation measurement consisting of three-modules. Firstly, since the distortion in the synthesized image mainly occurs in the region with high-frequency structure information, the Neutrosophic domain is employed to evaluate the degradation of local image structure. Secondly, by considering that the texture of the synthesized image might be damaged due to the warping of 2D image or the loss of information in the occlusion region, we evaluate the visual quality of local texture by using the features obtained from frequency domain. Thirdly, to measure the stretching distortion which is unique in the synthesized image, the visual quality of extracted stretching area is measured by entropy. Finally, a pooling operation is used to combine the quality scores of the three modules to obtain the final predicted quality score. Experimental results show that the performance of the proposed algorithm is competitive with state-of-the-art FR and no-reference image quality assessment metrics.

由于自由视点电视（FVT）的快速发展，基于深度图像的渲染（DIBR）技术已被广泛用于合成虚拟视点的图像。但是，合成图像中的变形类型与自然图像不同，例如不连续，闪烁，拉伸等。为了测量合成图像中发生的变形，我们提出了一种全参考（FR）质量评估方法由三个模块组成的局部变化测量。首先，由于合成图像的失真主要发生在具有高频结构信息的区域中，因此采用中智域来评估局部图像结构的退化。其次，通过考虑到合成图像的纹理可能会由于2D图像的扭曲或遮挡区域中的信息丢失而损坏，我们使用从频域获得的特征来评估局部纹理的视觉质量。第三，为了测量在合成图像中唯一的拉伸变形，通过熵测量提取的拉伸区域的视觉质量。最后，合并操作用于组合三个模块的质量得分，以获得最终的预测质量得分。实验结果表明，该算法的性能与最新的帧中继和无参考图像质量评估指标相比具有竞争力。第三，为了测量在合成图像中唯一的拉伸变形，通过熵测量提取的拉伸区域的视觉质量。最后，合并操作用于组合三个模块的质量得分，以获得最终的预测质量得分。实验结果表明，该算法的性能与最新的帧中继和无参考图像质量评估指标相比具有竞争力。第三，为了测量在合成图像中唯一的拉伸变形，通过熵测量提取的拉伸区域的视觉质量。最后，合并操作用于组合三个模块的质量得分，以获得最终的预测质量得分。实验结果表明，该算法的性能与最新的帧中继和无参考图像质量评估指标相比具有竞争力。