Image Brightness reduction by canceling bright areas using brightness level and reconstruction by geodesic dilation

Edgar Rubén Godoy Liseras, Julio César Mello Román, José Luis Vázquez Noguera, H. Legal-Ayala
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Abstract

Special devices capable of transforming continuous images into digital formats generate digital images. Image digitization enables treating, visualizing and storing images in a computer system. However, the high-intensity light captured by a device of this type can cause unwanted bright areas in the generated images. Since these bright areas can lead to image processing errors, manifested as a false appearance, their deletion and subsequent reconstruction can produce a more faithful image. A conventional approach, based on mathematical morphology, consists of reducing or eliminating unwanted image brightness by an erosion process. The image obtained through this method undergoes a reconstruction process based on successive geodesic dilations. In this paper, a new brightness reduction method is proposed. This method identifies bright areas by applying a defined brightness limit value to remove pixels with brightness values above it, but leaving the remaining pixels unmodified. Then, the image is reconstructed by the usual image reconstruction approach based on mathematical morphology. Compared to the conventional approach, the proposed method in this work enhances brightness, generating an image more faithful to the actual object.
通过亮度级别消除明亮区域来降低图像亮度,并通过测地线扩张进行重建
能够将连续图像转换为数字格式的特殊设备生成数字图像。图像数字化能够在计算机系统中处理、可视化和存储图像。然而,由这种类型的设备捕获的高强度光会在生成的图像中引起不必要的明亮区域。由于这些明亮区域可能导致图像处理错误,表现为虚假的外观,因此删除它们并随后重建可以产生更忠实的图像。基于数学形态学的传统方法包括通过侵蚀过程降低或消除不需要的图像亮度。通过该方法获得的图像经过基于连续测地线扩张的重建过程。本文提出了一种新的亮度降低方法。此方法通过应用定义的亮度极限值来去除亮度值高于该值的像素,而不修改其余像素,从而识别明亮区域。然后,采用常用的基于数学形态学的图像重构方法对图像进行重构。与传统方法相比,本文提出的方法提高了亮度,生成的图像更接近实际目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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