.png){kind=icon}
.png){kind=icon}
Return
A brightness-preserving two-dimensional histogram equalization method based on two-level segmentation
.png){kind=icon}
PRE
AI
DOI：10.1007/s11042-020-09265-y.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Histogram equalization (HE) is a classical enhancement method for image processing. However, conventional HE techniques have poor performance in terms of preserving the brightness and natural appearance of images, meaning they typically fail to produce satisfactory results. A novel two-dimensional HE method with two-level segmentation for refining image brightness is proposed in this paper. Additionally, a modified two-dimensional histogram is generated to determine the locations of main segmentation points based on neighborhood matrices. The weights of the absolute brightness differences between low and high local contrast regions in this two-dimensional histogram are adjustable. After separating images into two main areas based on main segmentation points, multiple sub-segmentation points are selected based on a novel criterion derived from the maximum value distribution of the double histograms. Experimental results for various test images demonstrate that the proposed method achieves excellent performance in terms of brightness preservation and image contrast enhancement.
Keywords:
Image enhancement
Two-dimensional histogram
Histogram equalization
Brightness-preserving
Two-level segmentation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3
Papers:
1.9W
Citations:
3.2W