A comparative analysis of various image enhancement techniques for facial images

• Published in: 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI) pp. 2279 - 2284
• Main Authors: Sharma, Neha, Saurav, Sumeet, Singh, Sanjay, Saini, Ravi, Saini, Anil K.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2015
• Subjects: Adaptive equalizers; AHE(Adaptive Histogram Equalization; AMBE(Absolute Mean Brightness Error); Brightness; CLAHE(Contrast Limited Adaptive Histogram Equalization); HE(Histogram Equalization); Histograms; Image enhancement; PSNR; PSNR(Peak Signal to Noise Ratio); Visualization
• ISBN: 9781479987900; 1479987905
• DOI: 10.1109/ICACCI.2015.7275957

Image enhancement is one of the most important pre-processing step used in a number of Computer Vision applications. Its importance can be judged by a number of image enhancement algorithms, which have been developed over the time for different applications. All these algorithms differ from one another in terms of processing speed, computational complexity, and quality of image and so on. Therefore, in order to exploit the usefulness of these algorithms it is necessary to have their good understanding. With this objective in mind, this paper presents a comparative analysis of six different commonly used image enhancement algorithms. The performance of these algorithms has been measured both quantitatively and qualitatively for different test images. From our analysis, we found that Modified CLAHE outperforms all other techniques in terms of PSNR and AMBE, which shows its better contrast enhancement and brightness preservation capabilities.