In the domain of contrast enhancement, contrast as well as detail retention are critical for human visualization and onward processing by any other computer based application. Contrast enhancement of an image with naturalness and preserved details is a challenge. In this paper, we propose a method using an edge-preserving smoothing operator approach, based on the weighted least squares (WLS) optimization. The detail and base layers are extracted using the WLS and median filters respectively. Base layer is a smooth layer of the image that contains large scale intensity changes and the detail layer captures the smaller scale details in the image. The layers are enhanced with a fine tuning between the rate of enhancement of the base and detail layers. It is vital to manage the level of enhancement in both the extracted layers as any mistune in the rate of enhancement may lead to severe distortion and addition of artifacts. Color correction is applied to the image to provide a higher-resolution improved image. The simulation results over 680 images from different datasets, show that the proposed method outperforms the existing methods in terms of qualitative and quantitative parameters.

在对比度增强领域，对比度和细节保留对于任何其他基于计算机的应用程序的人类可视化和后续处理至关重要。对具有自然性和保留细节的图像进行对比度增强是一项挑战。在本文中，我们提出了一种基于加权最小二乘 (WLS) 优化的使用边缘保留平滑算子方法的方法。分别使用 WLS 和中值滤波器提取细节层和基础层。基础层是图像的平滑层，包含大尺度强度变化，细节层捕获图像中较小尺度的细节。通过在基础层和细节层的增强率之间进行微调来增强这些层。管理两个提取层中的增强级别至关重要，因为增强率的任何失调都可能导致严重的失真和伪影的添加。对图像应用色彩校正以提供更高分辨率的改进图像。来自不同数据集的 680 幅图像的模拟结果表明，所提出的方法在定性和定量参数方面优于现有方法。