摘要：

适用于带噪声彩色图像增强的方法少，而应用灰度图像的增强方法，不仅增强噪声，而且会产生色彩偏离。基于此，提出在HSV色彩空间上的降噪与增强方法。根据人眼视觉系统对亮度的变换敏感性大于色度和饱和度的变换敏感性，以及图像噪声只对亮度和饱和度产生影响，将真彩图像由RGB空间变换到HSV空间，保持色度通道不变，对亮度通道进行小波变换，直接对J尺度下的低频信息进行动态范围的压缩，对各尺度下的高频信息进行基于贝叶斯估计阈值的降噪处理。对饱和度通道，利用得到的降噪公式进行降噪处理，将图像变换到RGB 空间。仿真实验证实，增强后的真彩图像包含噪声少，色彩基本无偏差，图像动态范围压缩良好。

关键词: 真彩图像, HSV空间, 小波变换, 降噪和增强, 贝叶斯估计

Abstract:

In the light of few enhancement method for real color images with noise and the application of gray-scale image enhancement methods in the three-channel of images (R,G,B), on the one hand, increasing noise, on the other hand, tending to have a color deviation, this paper proposes a method of image denoising and enhancement in HSV space. According to influence of luminance and saturation by noise and more sensitivity of luminance by human visual system than others, it transforms the color image from RGB space to HSV space, then maintains hue channel unchanged, decomposes luminance channel using wavelet transform and directly compresses dynamic range of the J-scale low frequency information, uses Byes-estimation threshold to denoise in all scale high frequency information. Saturation channel is denoised by some formula. It transforms into a real color images from HSV space to RGB space. Experiments show that image has a good dynamic compression range and slight color deviation, which improves the visual effects and the true effects of color.

Key words: real color image, HSV space, wavelet transform, denoising and enhancement, Bayes-estimation

中图分类号: 

• TN919.81