Rock Image Contrast Enhancement Method Based on Improved De-sharpening Mask

Meizheng Ge, Qiong Liu
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引用次数: 0

Abstract

In engineering applications, traditional methods are usually used to acquire microscopic images, and due to objective factors such as uneven acquisition equipment and uneven illumination, there may be problems such as unclear acquisition images and insufficient local exposure. Traditional de-sharpening mask image enhancement algorithms are suitable for enhancing the edges and details of microscopic images, but are extremely sensitive to noise and do not enhance contrast and detail at the same time. In this paper, an improved sharpening masking algorithm is proposed, which sharpens the edges of rock images in the brightness channel of HSV color space, uses the difference between the non-local mean filter image and the original image to achieve high-frequency components, adaptively enhances the high-frequency components, improves the problem of image light unevenness through the contrast enhancement algorithm, and superimposes it with high-frequency components to effectively enhance the image. Experimental results show that the image processed by the algorithm has outstanding details and clear textures, which better suppresses the amplification of noise.
基于改进去锐化蒙版的岩石图像对比度增强方法
在工程应用中,通常采用传统方法获取微观图像,由于采集设备不均匀、光照不均匀等客观因素,可能存在采集图像不清晰、局部曝光不足等问题。传统的去锐化掩膜图像增强算法适用于增强微观图像的边缘和细节,但对噪声极为敏感,不能同时增强对比度和细节。本文提出了一种改进的锐化掩蔽算法,在HSV色彩空间亮度通道对岩石图像边缘进行锐化,利用非局部均值滤波图像与原始图像的差异实现高频分量,自适应增强高频分量,通过对比度增强算法改善图像光照不均匀问题。并将其与高频分量叠加,有效增强图像。实验结果表明,该算法处理后的图像细节突出,纹理清晰,较好地抑制了噪声的放大。
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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