원문정보
초록
영어
Histogram Equalization (HE) is a simple and effective image enhancement technique.But, it tends to change the mean brightness of the image to the middle level of the permitted range, and hence is not a very suitable for consumer product. While preserving the original brightness is essential to avoid annoying artefacts. To preserve brightness and to enhance contrast of images, numerous methods are introduced, but many of them present unwanted artefacts such as intensity saturation, over-enhancement and noise amplification. In the present paper, available histogram equalization based methods are reviewed and compared with image quality measurement (IQM)tools such as Absolute Mean Brightness Error (AMBE) to assess brightness preserving and Peak Signal-to-Noise Ratio (PSNR) to evaluate contrast enhancement.
목차
1. Introduction
1.1. Histogram Equalization Methods
2. Histogram Equalization based Techniques
2.1. Bi-Histogram Equalization Methods
2.2. Multi Histogram Equalization Methods
2.3. Clipped Histogram Equalization Methods
3. Image Quality Measurement Tools
3.1 . Absolute Mean Brightness Error (AMBE)
3.2. Peak Signal-to-Noise Ratio (PSNR)
4. Results and Discussion
5. Conclusions
References