The detailed examination of low contrast image is a challenging issue. Thus, it makes difficult for the viewer to bring out the detailed features of the image. Histogram equalization (HE) is an efficient way to intensify the contrast of images. However, classical HE techniques result in immoderate intensification. Hence, an efficient contrast enhancement algorithm called quadrant dynamic clipped HE with gamma correction is proposed. This transformation addresses both over‐enhancement and fine detail preservation, which ensures no false contouring. In the proposed method, histogram of the input image is partitioned into four sections using its mean value. Histogram clipping and gamma correction is used to control the color enhancement rate. Then, clipped subhistogram is equalized independently and then they combined together to form an enhanced image. The performance assessment of the proposed and other existing methods is evaluated in terms of entropy, contrast, colorfulness, and saturation. Test results demonstrates that the proposed method outperforms the other existing HE methods in terms of preserving entropy, colorfulness, saturation, and obtaining uniform degree enhancement.

中文翻译：

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带有伽玛校正的象限动态限幅直方图均衡，用于彩色图像增强

低对比度图像的详细检查是一个具有挑战性的问题。因此，观看者难以带出图像的详细特征。直方图均衡（HE）是增强图像对比度的有效方法。但是，经典的HE技术会导致强度减弱。因此，提出了一种有效的对比度增强算法，称为带有伽马校正的象限动态限幅HE。这种转换既解决了过度增强又保留了精细的细节的问题，从而确保了不虚假的轮廓。在提出的方法中，输入图像的直方图使用其平均值分为四个部分。直方图裁剪和伽玛校正用于控制颜色增强率。然后，裁剪的亚直方图被独立均衡，然后将它们组合在一起以形成增强的图像。在熵，对比度，色彩和饱和度方面评估了所提出方法和其他现有方法的性能。测试结果表明，该方法在保持熵，色彩，饱和度和获得均匀度增强方面优于其他现有的HE方法。