Infrared-Image-Enhancement

代码说明：

  针对基于小波变换的红外图像增强方法视觉效果不够理想的缺点, 提出了一种基于平稳小波变换和Retinex 的红外图像增强方法, 利用Retinex 增强算法增强图像的视觉效果, 并改善其亮度均匀性。首先, 对红外图像经平稳小波变换后的最大尺度低频子带图像进行多尺度Retine x 增强 然后, 利用贝叶斯萎缩阈值法对高频子带图像进行阈值去噪, 并根据低频子带图像的局部对比度和模糊规则计算高频子带的增益系数, 从而得到增强后的高频子带图像 最后, 由低频子带图像和高频子带图像重构得到增强后的图像。针对大量图像进行了实验和增强效果的定性与定量评价, 并与双向直方图均衡法、二代小波变换法、Curvelet 变换法和多尺度Retinex法作了比较。结果表明, 所提出的方法增强了图像细节, 抑制了噪声, 并明显改善了图像的整体视觉效果。(As infrared image enhancement method based on wavelet transformation has the problem of unperfect visual effect , and Retinex enhancement algorithm can enhance visual effect of the image by improving brightness uniformity , amethod based on stationary wavelet transformation and Retinexis proposed.Firstly , the infrared image is decomposed into high-frequency detail and low-frequency approximation components at various resolutions, and the low frequency subband image of the largest scale is enhanced by multiscale Retinex algorithm.Then, the highfrequency subband images are denoised by Bayesian shrinkage method, and the gain coefficients of high-frequency subbands are available by calculating the local contrast of the enhanced low-frequency subband based on fuzzy rules to get the enhanced high-frequency subband images .Finally, the enhanced image is reconstructed by the low-frequency subband and high-frequency subbands .Experiments with qualitative and quantitative uation are carried ou)

文件列表：

Infrared Image Enhancement.pdf,502090,2016-12-23