基于Matlab的图像对比度增强方法比较

Comparison of Contrast Enhancement Methods Based on Matlab

摘要: 实际采集的图像最普遍的弱点是对比度不理想，也即客体与背景的灰度级相差太小，难以辨别；此外，为减少噪声而进行平滑化后，会使图像对比度进一步缩小。图像对比度增强处理的作用就在于增大图像的对比度，以使图像黑白较为分明，细节清晰可辨。它是改善图像的视觉效果，使之更适合于人眼的观察判断或计算机分析处理的一种比较简单有效的理论、经验和技巧相结合的技术手段，在图像增强技术中占有重要地位，并在实际中(如红外、雷达、卫星遥感、生物医学、工业视觉、字符、新闻等图像)得到广泛应用。图像对比度增强大多在空域上直接进行，其方法大都是面向问题的，当处理一幅可视图像时，常用主观视觉评定经过对比度增强后的图像质量。目前还没有一种通用而有效的定量评价准则。因此，实际应用中要找到一种行之有效的方法常需针对具体给定的图像广泛地进行实验，再从中选择最为合适的一种或者综合其中的几种。

Abstract: The most common weakness of the actual images is that the contrast is not ideal, that is, the gray-scale difference between the object and the background is too small to distinguish. In addition, the image contrast will be further reduced after smoothing to reduce noise. The function of image contrast enhancement processing is to increase the contrast of the image, so that the black and white of the image are more distinct, and the details are clearly distinguishable. It is a simple effective theory that improves the image visual effect, making it more suitable for the human eye observation or computer analysis, with the combination of experience, skills, and technology, plays an important role in image enhancement technology, and is widely used in practice, such as infrared, radar, satellite remote sensing, biomedical, industrial, visual images, characters, news, and so on. Image contrast enhancement is mostly carried out directly in airspace, and its methods are mostly problem-oriented. When processing a visual image, subjective vision is often used to evaluate the image quality after contrast enhancement. At present there is no general and effective quantitative evaluation criterion. Therefore, to find an effective method in practical application, it is often necessary to conduct extensive experiments on specific given images, and then select the most appropriate one or combine several of them.