The problem of image quality assessment based on hybrid multi-distortion remains challenging in the computer vision field. Unmanned aerial vehicle (UAV) images are affected by the imaging conditions of hybrid multi-distortion. Accurate evaluation of image quality is critical in the performance of image quality assessment. An evaluation model of distance measurement based on natural scene statistics is introduced and improved

and a blind image quality assessment method for UAV with multi-distortion is proposed. The features of image quality sensitivity are studied and extracted from three different aspects of image structure

information integrity

and color. In reality standards of surveying and mapping an image library for an original image

Mualem-van Genuchten characteristic parameters are obtained as reference to solve the problem of blind evaluation lacking a training set. The UAV image quality database is constructed with a real fly image as sample

and the data set and evaluation reference are provided for studying the problems. In view of the constructed database

this paper makes a comparison between the subjective and objective consistency and the running time of the algorithm. Compared with other classical algorithms

the subjective and objective consistency of this algorithm is higher

reaching more than 0.8

Running time is faster

for 1.2 s. In addition

this paper also gives the effect of block size on the algorithm and the evaluation results of single feature to UAV images. This image block size and image feature which are selected by the algorithm are proved to meet the needs of quality evaluation. In this study

a comprehensive model of quality evaluation for the multi-distortion of UAV images is constructed. This model can meet the requirements of UAV image quality.