We present a novel technique to distinguish between an original image and its histogram equalized version. Histogram equalization and superpixel segmentation such as SLIC (simple linear iterative clustering) are very popular image processing tools. Based on these two concepts, we introduce a method for finding whether an image (grayscale) is histogram equalized or not. Because sometimes we see images that look visually similar but they are actually processed or changed by some image enhancement process such as histogram equalization. We can merely infer whether the image is dark, bright or has a small dynamic range. Moreover, we also compare the result of SLIC superpixels with three other superpixel segmentation algorithms namely, quick shift, watersheds, and Felzenszwalb’s segmentation algorithm

我们提出了一种新颖的技术来区分原始图像及其直方图均等化版本。直方图均衡和超像素分割（例如SLIC（简单线性迭代聚类））是非常流行的图像处理工具。基于这两个概念，我们介绍一种用于查找图像（灰度）是否等于直方图的方法。因为有时我们看到的图像看上去很相似，但是实际上是通过某些图像增强过程（例如直方图均衡化）来处理或更改的。我们只能推断图像是暗的，亮的还是动态范围小。此外，我们还将SLIC超像素的结果与其他三种超像素分割算法（即快速平移，分水岭和Felzenszwalb的分割算法）进行了比较