Aiming at the process of medical diagnosis, many problems such as unclear images and low contrast are often caused by noise and interference in the process of medical image acquisition and transmission. This article proposes a new image enhancement method that combines the wavelet domain with the spatial domain. First, we input two identical images (Both of the identical images are original images.) in which the first image is enhanced by histogram equalization. Then, the two images are divided into four sub‐images by a two‐dimensional wavelet transform. The average of the low‐frequency coefficients of the low‐frequency sub‐images of the two images is taken as the low‐frequency coefficients of the final reconstruction. Second, aiming at the problem that the contrast may be too low, the fourth high‐frequency sub‐image is blurred (sharpened) twice. The fourth high‐frequency sub‐image after blurring is denoised by median filtering. Finally, the four sub‐images are fused to obtain the enhanced image. The experimental results show that the peak signal‐to‐noise ratio, structural similarity, and processing time of the proposed algorithm are better than those of other contrast algorithms, especially the processing time. These objective indicators show that the proposed algorithm can not only effectively suppress noise but also significantly enhance the contrast. Subjectively, compared with other algorithms, the proposed algorithm achieves a better visual effect and greatly reduces the processing time.

中文翻译：

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一种高效、高质量的医学CT图像增强算法

针对医学诊断过程中，在医学图像采集和传输过程中，往往由于噪声和干扰等原因造成图像不清晰、对比度低等诸多问题。本文提出了一种新的图像增强方法，将小波域与空间域相结合。首先，我们输入两个相同的图像（两个相同的图像都是原始图像。）其中第一幅图像通过直方图均衡化进行了增强。然后，通过二维小波变换将两幅图像分成四个子图像。取两幅图像的低频子图像的低频系数的平均值作为最终重建的低频系数。其次，针对对比度可能过低的问题，对第四个高频子图进行了两次模糊（锐化）处理。模糊后的第四个高频子图像通过中值滤波去噪。最后，将四个子图像融合以获得增强图像。实验结果表明，所提算法的峰值信噪比、结构相似度和处理时间均优于其他对比算法，尤其是处理时间。这些客观指标表明，所提出的算法不仅可以有效抑制噪声，而且可以显着增强对比度。主观上，与其他算法相比，本文算法取得了更好的视觉效果，大大减少了处理时间。实验结果表明，所提算法的峰值信噪比、结构相似度和处理时间均优于其他对比算法，尤其是处理时间。这些客观指标表明，所提出的算法不仅可以有效抑制噪声，而且可以显着增强对比度。主观上，与其他算法相比，本文算法取得了更好的视觉效果，大大减少了处理时间。实验结果表明，所提算法的峰值信噪比、结构相似度和处理时间均优于其他对比算法，尤其是处理时间。这些客观指标表明，所提出的算法不仅可以有效抑制噪声，而且可以显着增强对比度。主观上，与其他算法相比，本文算法取得了更好的视觉效果，大大减少了处理时间。