Block-based multi-scale image enhancement method for industrial inspection system
Viacheslav Voronin, Nikolay Gapon, Marina M. Zhdanova, Evgeny A. Semenishchev, Alexander A. Zelensky, Yurii V. Ilyukhin · 2023
Automated inspections and intelligent image processing optimize quality control processes. Images captured in the industrial inspection system have low contrast and faint color. Many enhancement algorithms have recently been proposed to enhance visibility and restore color. We present a new image enhancement algorithm based on multi-scale block-rooting processing. The proposed method based on the frequency-domain coefficient correction of a set of images followed by their fusion based on the Laplacian pyramid. A new stage is presented in obtaining a local-global estimate of high-contrast images, also used in the general fusion model. The main idea is that enhancing the contrast of an image would create more high-frequency content in the enhanced image than in the original image. The experiment results on the test dataset confirmed the high efficiency of the proposed enhancement method compared to the state-of-the-art techniques for industrial inspection systems.