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This article presents an algorithm for determining reference brightness correction coefficients to improve image quality. The algorithm utilizes a combination of statistical analysis and image processing techniques to identify and correct brightness discrepancies in digital images. By establishing a robust and efficient method for calculating these coefficients, the algorithm aims to enhance the overall visual fidelity of images across various applications, such as photography, medical imaging, and remote sensing. The proposed algorithm demonstrates its effectiveness through experimental results and comparisons with existing methods, highlighting its potential for practical implementation in image processing workflows. In the world, the filtering of digital images by the convolution method with a pulse characteristic in the spectral region scientific research is being conducted to improve the quality level of digital television images, methods for modeling filtration processes and highly efficient control systems in a number of priority areas, including: on the formation of mathematical models of filtration processes, improving the methods of wavelet, Fourier, Haar, Walsh-Hadamard, Karhunen-Loev in increasing the clarity and brightness of images based on linear and nonlinear differential equations; creation of methods for eliminating additive, pulsed and adaptive-Gaussian types of noise in images using additive and adaptive filtering; methods of algorithms and software for introducing intra-frame and interframe image transformations; methods of adaptive brightness system control using the Chebyshev matrix series; methods of gradient, static and Laplace methods for image segmentation and dividing it into contours; formation of criteria and conditions for evaluating image quality. Conducting scientific research in the above research areas confirms the relevance of the topic of this article.
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