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Infrared image quality assessment based on fractal dimension method

The operation and observation experience of users is affected by the quality of infrared images which are collected by infrared imager. And image quality is a significant indicator for the performance of image processing algorithm and the optimization of system parameters as well. An image quality reduced reference assessment model is put forward to evaluate the degree of infrared image quality reduction. The detail characteristic of infrared image texture is extracted by the fractal dimension analysis method proposed in this paper as the representation of image quality. The method computes the fractal dimension of every pixel one by one with a multi-scale window over the entire image to get the information of corresponding image block. A quality information image is mapped from the fractal dimension of all pixels to describe the infrared image quality. The parameters of the quality information image combined with the peak SNR of original infrared image are adopted as the metric of infrared image quality. The method can be embedded into image processing system to optimize image processing algorithms and parameters settings, and provide reference for fault diagnosis.