高光像梯度校正模型的比较效率分析

2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T) Pub Date : 2019-10-01 DOI:10.1109/PICST47496.2019.9061356

Kirill Smelyakov, Mykyta Hvozdiev, A. Chupryna, Denys Sandrkin, V. Martovytskyi

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引用次数: 14

摘要

本文对比分析了高光数字图像中最常用的能自动适应不同亮度尺度的梯度校正模型(幂、指数和对数)的应用情况，讨论了它们在实际应用中的特点，并建立了高光图像的改进实验。在实验中，使用不同的渐变校正模型和不同的参数对测试图像进行了修正，这有助于显示这种修正的实用价值，并给出了图像增强系数，以对比分析输入参数对最终结果的影响。结合实验结果，对模型的实际应用进行了分析和建议，有助于解决数字图像质量改进的实际应用任务

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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Comparative Efficiency Analysis of Gradational Correction Models of Highly Lighted Image

The paper provides a comparative analysis of the application of the most demanded gradational correction models (power, exponential and logarithmic) of a highly lighted digital image, which capable of automatic adaptation to different brightness scales, discusses the features of their practical application, sets up an experiment to improve the highly lighted photo. In the experiment, the test image is modified with use of different gradation correction models and different parameters, this helps to show the practical value of such modifications and the coefficient of image enhancement is given to provide comparative analysis of influence of input parameters to final result. After considering the results of the experiment, analysis and recommendations for the practical use of the models are given which helps to solve actual applied tasks of digital image quality improvement

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来源期刊

2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T)

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