A novel approach for contrast enhancement based on Histogram Equalization

Abstract

Histogram based techniques is one of the important digital image processing techniques which can be used for image enhancement. One of the advantages of histogram based techniques is simplicity of implementation of the algorithm. Also it should be mentioned that histogram based techniques is much less expensive comparing to the other methods. Histogram based techniques for image enhancement is mostly based on equalizing the histogram of the image and increasing the dynamic range corresponding to the image. Histogram Equalization (HE) method has two main disadvantages which affect efficiency of this method. For solving the above problems, some techniques have proposed for example using Bi Histogram Equalization (BHE) algorithm instead of Histogram Equalization (HE). It should be mentioned that Bi Histogram Equalization (BHE) is one of the best proposed algorithm which has proposed until now. This paper presents a novel algorithm for contrast enhancement based on Histogram Equalization (HE). Our proposed algorithm applies some preprocessing steps on the histogram corresponding to the image and then applies histogram equalization. We have applied our proposed algorithm on a database which includes 220 normal images and results are promising. Our proposed method has better results comparing with Bi Histogram Equalization (BHE) algorithm based on visual criterion and a mathematical criterion.

Underwater image quality enhancement through composition of dual-intensity images and Rayleigh-stretching

“…Histogram Figure 6 The visual process of contrast correction of the proposed method. equalization (HE) (Singhai and Rawat 2007;Yeganeh et al 2008;Senthilkumaran and Thimmiaraja 2014;Arici et al 2009) will be also used in comparison as it is the basic technique in histogram modification that most commonly used by previous researchers in image processing. The proposed method is designed to improve the underwater image in terms of contrast, noise reduction, and image details, quantitative measurement such as entropy, mean square error (MSE), and peak signal to noise ratio (PSNR) are used to evaluate the output image.…”

Cardiac CT Image Enhancement Method Based on Prior Knowledge

“…We processed each cardiac CT image by histogram equalization (HE) [5], common contrast enhancement and the method proposed in this paper, and made a lateral correlation between the results. See Fig.1 for the specific experimental results.…”

A Detail Enhancement Algorithm of Infrared Images Based on Second-generation Wavelet Cumulative Probability

“…The algorithm uses the second-generation wavelet integer enhancing algorithm (i.e., second-generation wavelet integer transform) [9] , conducts mono-layer decomposition for the infrared images, the specific algorithm is described as follows:…”