Image quality assessment (IQA) plays an important role in digital image forensics. Due to the occurrence of contrast distortion during image acquisition and manipulation, IQA for contrast is a major issue. And it is vital for benchmarking and optimizing the image tampering detection and contrast-enhancement algorithms. In this paper, a new no-reference/blind image quality assessment (IQA) metric is proposed for evaluating image contrast. This research seeks for the inter-relationship between contrast distortion and visual perception quality. The comprehensive quality metric is obtained by combining local binary pattern (LBP) descriptor on gradient domain with color moment on HSV color space. And a prediction model is trained with support vector regression (SVR). Extensive analysis and cross validation are performed on four contrast relevant image databases, which validates the superiority of our proposed blind technique over state-of-the-art no-reference IQA methods.

图像质量评估（IQA）在数字图像取证中起着重要作用。由于在图像获取和处理过程中发生对比度失真，因此对比度的IQA是一个主要问题。这对于基准测试和优化图像篡改检测以及对比度增强算法至关重要。本文提出了一种新的无参考/盲图像质量评估（IQA）指标，用于评估图像对比度。这项研究寻求对比度失真和视觉感知质量之间的相互关系。综合质量度量是通过将梯度域上的本地二进制模式（LBP）描述符与HSV颜色空间上的色矩相结合而获得的。并使用支持向量回归（SVR）训练预测模型。