Abstract
In order to solve the problem of low contrast and fuzzy detail in infrared image, we propose an infrared image enhancement method based on multi-scale and adaptive bi-interval histogram equalization with details. The method mainly consists of four parts: details enhancement, contrast stretch, edge enhancement and reconstruction of enhancement images. Firstly, the multi-scale convolution is used to enhance the details of image; Secondly, taking maximize the variance between classes and minimize the variance as fitness function and solved the threshold of the infrared image by genetic algorithm, then dividing the infrared image into two sub-intervals according to the threshold. After that, the bi-interval histogram equalization with details is applied to enhance the global contrast, at the same time, using the mean square deviation and average gray equalization to improve the brightness of the image. Finally, the enhanced image by adaptive bi-interval histogram equalization with details and the image processed by adaptive limited Laplace operator are fused by linear weighting to reconstruct the final enhancement image. The experimental results show that the proposed method can outperform state-of-the-art ones in both qualitative and quantitative comparisons.
Highlights
Infrared imaging technology is widely used in aerospace, maritime rescue, and military target detection [1]–[3]
The information entropy (IE) of the images processed by other methods is higher than that of the original image and the IE of the images processed by our method is the largest, which indicates that HEEF [32] and Wan [31] will reduce the contrast of the image, other methods can improve the contrast of the image and the image processed by this method is higher
The average gradient (AG) of the image A-F processed by our method is the largest than that of the original image and the other five algorithms in AG, IE and enhancement by entropy (EME), indicating that the image processed by our method has the largest contrast, the most abundant detailed information and the best visual effect compared with other five methods
Summary
Infrared imaging technology is widely used in aerospace, maritime rescue, and military target detection [1]–[3]. The contrast of infrared image is low and the texture details are fuzzy. The main reason is that the infrared ray will be affected by the atmospheric thermal radiation due to the distance between the target and the sensors in the scene is far away [4], [5]. In order to improve the contrast of infrared image and highlight the target details, image enhancement is an effective method [2], [4], [35]. In Fig., we give examples of the original infrared images and their enhanced effects in different scenes. The low-quality images with blurred details and low contrast are shown in the top row of Fig., which reduce the visual effect of the image and affect people’s recognition and perception of the target. The infrared images enhanced by our method are shown in the bottom row
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