Recent years have witnessed a broader range of applications of image
processing technologies in multiple industrial processes, such as smoke
detection, security monitoring, and workpiece inspection. Different kinds of
distortion types and levels must be introduced into an image during the
processes of acquisition, compression, transmission, storage, and display,
which might heavily degrade the image quality and thus strongly reduce the
final display effect and clarity. To verify the reliability of existing image
quality assessment methods, we establish a new industrial process image
database (IPID), which contains 3000 distorted images generated by applying
different levels of distortion types to each of the 50 source images. We
conduct the subjective test on the aforementioned 3000 images to collect their
subjective quality ratings in a well-suited laboratory environment. Finally, we
perform comparison experiments on IPID database to investigate the performance
of some objective image quality assessment algorithms. The experimental results
show that the state-of-the-art image quality assessment methods have difficulty
in predicting the quality of images that contain multiple distortion types.

近年来，图像处理技术在多个工业过程中的应用范围日益广泛，为验证现有的图像质量评估方法的可靠性，我们建立了一个新的工业过程图像数据库（IPID），其中包含 3000 个经过不同程度畸变处理的图片，并进行了主观测试以收集其主观质量评分，在 IPID 数据库上进行对比实验以研究一些客观图像质量评估算法的性能，实验结果表明，最先进的图像质量评估方法在预测包含多种失真类型的图像质量方面存在困难。