@article{Serdiuk_Berkut_Sirik_2019, title={THE METHOD OF IMPROVING FOGGED IMAGES VISIBILITY AND ITS USING IN THE PROCESSING IMAGES COMPUTER SYSTEM}, url={http://ric.zntu.edu.ua/article/view/193901}, DOI={10.15588/1607-3274-2019-4-16}, abstractNote={Context. Presence of fog and haze on digital images may cause problems in processes of recognition, tracking, classification of objects.<br />Thus methods for removing fog and improving visibility of objects in images obtained under poor visibility conditions are in demand in<br />many computer vision problems. In foggy weather, contrast and color of an image get worse. Fog removal is often accompanied by artifacts<br />in the image and color distortion. Therefore, it is relevant to seek methods for correct assessing presence and removal of fog while preserving<br />image details and colors and developing appropriate methods for blurred images processing.<br />Objective. The purpose of this research is to find effective approaches to solving the problem of removing fog and haze from digital images<br />and implementing them in a digital image processing computer system [1].<br />Method. Main stages of image processing are performed on the intensity channel, which helps to preserve colors. The proposed approach<br />keeps the values of the processed pixels in an acceptable range, which allows better preservation of image details. Frequency filters<br />are used to evaluate the transmission map. In a modified method, fog density is estimated using a neural network.<br />Results. The method of removing fog and haze from single image is proposed. This method effectively improves the objects visibility,<br />preserves details and colors in the image. A modification of the method with another fog density estimation method is also proposed. The<br />presented methods were implemented in a computer system [1].<br />Conclusions. The proposed method and its modification effectively remove fog and haze from single image and improve the objects<br />distinguishability in them. The implementation of these methods in a computer image processing system [1] has expanded the functionality<br />of the system and increased its ability to improve the quality of images obtained under poor visibility conditions. The system can be used for<br />preliminary image processing to prevent errors in further operation of computer vision algorithms.}, number={4}, journal={Radio Electronics, Computer Science, Control}, author={Serdiuk М. Е. and Berkut, V. G. and Sirik, S. F.}, year={2019}, month={Nov.}, pages={166–176} }