基于双域分解的图像增强算法

为解决图像增强中对比度提高与噪声抑制的矛盾，本文提出了一种基于双域分解的图像增强算法，同步实现图像对比度提高与噪声抑制.文中详述了空域分解、分层图像空域增强与变换域降噪、分层图像合成三个主要环节的原理、方法.首先，高斯滤波器将图像分解为基础层和细节层，实现对比度提高与噪声抑制的解耦合；其次，带校正功能的单尺度Retinex和硬阈值收缩的非下采样剪切波降噪算法同步实现基础层的增强和细节层的降噪；最后，分层图像合成、灰度数值延展和微分算子强化，实现合成图像的灰度延展与细节加强，确保增强图像的颜色均匀、细节突出.实验表明，本文算法提高图像对比度和抑制噪声的性能优于其他九种算法.

Image Enhancement Algorithm Based on Dual Domain Decomposition

To solve the contradiction between contrast enhancement and noise suppression in image enhancement,an image enhancement algorithm based on dual domain decomposition (IEDD) is proposed.The principles and methods including spatial domain decomposition,layered spatial images enhancement and transform domain noise reduction,and layered images synthesis are described in detail.Firstly,the image is decomposed into a base layer and a detail layer by a Gaussian filter,that decouples the contrast enhancement and noise reduction.Next,in order to realize the enhancement of base layer and noise reduction of detail layers synchronously,the single-scale Retinex with correction function and the nonsubsampled shearlet denoising algorithm with hard threshold shrinkage are implemented.Finally,to ensure the uniform color and the outstanding detail of the composite image,layered image fusion,gray value extension and differential operator detail enhancement are implemented,realizing the grayscale extension and detail enhancement of the composite image.Experiments show that the performance of the proposed algorithm is better than other nine algorithms in improving image contrast and suppressing noise.