• Journal of Internet Computing and Services
• /
• v.10 no.3
• /
• pp.173-185
• /
• 2009

This paper proposes two new image contrast enhancement methods, RSWHE (Recursively Separated and Weighted Histogram Equalization) and RSWHS (Recursively Separated and Weighted Histogram Specification). RSWHE is a histogram equalization method based on histogram decomposition and weighting, whereas RSWHS is a histogram specification method based on histogram decomposition and weighting. The two proposed methods work as follows: 1) decompose an input histogram based on the image's mean brightness, 2) compute the probability for the area corresponding to each sub-histogram, 3) modify the sub-histogram by weighting it with the computed probability value, 4) lastly, perform histogram equalization (in the case of RSWHE) or histogram specification (in the case of RSWHS) on the modified sub-histograms independently. Experimental results show that RSWHE and RSWHS outperform other methods in terms of contrast enhancement and mean brightness preservation as well.

• IEIE Transactions on Smart Processing and Computing
• /
• v.3 no.6
• /
• pp.358-365
• /
• 2014

This paper proposes a method that reduces the flickering effect caused by A-GLG (Adaptive Gray-Level Grouping) during video contrast enhancement. Of the GLG series, A-GLG shows the best contrast enhancement performance. The GLG series is based on histogram grouping. Histogram grouping is calculated differently between the continuous frames with a similar histogram and causes a subtle change in the transformation function. This is the reason for flickering effect when the video contrast is enhanced by A-GLG. To reduce the flickering effect caused by A-GLG, the proposed method calculates a modified transformation function. The modified transformation function is calculated using a previous and current transformation function applied with a weight separately. The proposed method was compared with A-GLG for flickering effect reduction and video contrast enhancement. Through the experimental results, the proposed method showed not only a reduced flickering effect, but also video contrast enhancement.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.2
• /
• pp.76-85
• /
• 2004

In this paper, the contrast enhancement method of thermal image is proposed and it is the plateau equalization algorithm using local histogram for the real time display of infrared imagery. Through hardware implementing, its practicality and adequacy are proved. Examinations are executed to verify the effect of contrast enhancement by bright control and contrast control automatic to the plateau value in the manual mode, and that verified the effect of contrast enhancement in the automatic mode and the practicality in the real system. According to the experiment results, the proposed "the application of local histogram and plateau equalization algorithm for contrast enhancement of real time thermal image"in this dissertation is the verified method for the thermal imaging contrast enhancement.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.12
• /
• pp.5127-5133
• /
• 2010

In this paper, an efficient contrast enhancement algorithm using histogram specification is proposed. Histogram equalization and its modified methods have been effective techniques for contrast enhancement. However, they often result in excessive contrast enhancement. Besides conventional histogram specification also has a problem to get the desired histogram. We propose a method that utilizes a simple high frequency filter to get the desired histogram. The proposed technique not only produces better visual results than conventional contrast enhancement techniques, but is also adaptively adjusted to the statistical characteristics of the image.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.01a
• /
• pp.83-86
• /
• 2019

Histogram equalization is extensively used for image contrast enhancement in various applications due to its effectiveness and its modest functions. In image research, image enhancement is one of the most significant and arduous technique. The image enhancement aim is to improve the visual appearance of an image. Different kinds of images such as satellite images, medical images, aerial images are affected from noise and poor contrast. So it is important to remove the noise and improve the contrast of the image. Therefore, for this purpose, we apply a median filter on MR image as the median filter remove the noise and preserve the edges effectively. After applying median filter on MR image we have used intensity transformation function on the filtered image to increase the contrast of the image. Than applied the histogram equalization (HE) technique on the filtered image. The simple histogram equalization technique over enhances the brightness of the image due to which the important information can be lost. Therefore, adaptive histogram equalization (AHE) and contrast limited histogram equalization (CLAHE) techniques are used to enhance the image without losing any information.

• Journal of Broadcast Engineering
• /
• v.19 no.1
• /
• pp.96-108
• /
• 2014

In case of contrast of the image enhancement by using the conventional histogram equalization, over-enhancement, false contouring and distortion such as the details disappearance of the image occurs due to the excessive brightness change. Especially, these distortion appears when the brightness distribution is concentrated in a particular brightness level. In order to solve these problems, improved histogram equalization methods to transform the input histogram by clipping using threshold have been proposed, but contrast enhancement effect is reduced because it does not consider the characteristics of the input image's histogram to apply the same threshold for the entire histogram, and unnatural image is obtained because it does not retain the characteristics of the image. In this paper, to solve the problems of existing methods, we propose new equalization method that suppress excessive brightness changes by applying to the differential compression according to the histogram frequency, and maintain the characteristics of the input image. In addition, we propose a more effectively method to improve contrast by controlling the strength of the compression ratio depending on the characteristics of the input image.

• Journal of the Korean Society of Industry Convergence
• /
• v.13 no.1
• /
• pp.23-30
• /
• 2010

This paper presents a histogram equalization based on the nonlinear transformation function for enhancing the quality of medical images. The nonlinear transformation function is applied to adaptively equalize the brightness of the image according to its intensity level frequency. The logistic function is used as a nonlinear transformation function, which is calculated by only using the intensity level with maximum frequency and the maximum intensity level in an histogram, and the total number of pixels. The proposed method has been applied for equalizing 8 medical images with a different resolution and histogram distribution. The experimental results show that the proposed method has the superior enhancement performances compared with the conventional histogram equalization. And the proposed histogram equalization can be used in various multimedia systems in real-time.

• Journal of the Semiconductor & Display Technology
• /
• v.14 no.4
• /
• pp.50-55
• /
• 2015

This paper proposes a new histogram partition stretching and shrinking method for infrared image enhancement. The proposed method divides the histogram of an input image into three partitions according to its mean value and standard deviation. The method stretches both the dark partition and the bright partition of the histogram, while it shrinks the medium partition. As the result, both the dark part and the bright part of the image have more brightness levels. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using various infrared images. The results show that the proposed algorithm is successful for the infrared image enhancement.

• Journal of Korea Multimedia Society
• /
• v.11 no.6
• /
• pp.737-745
• /
• 2008

In this paper, a novel neighborhood metric of histogram equalization (HE) algorithm for contrast enhancement is presented. We present a refinement of HE using neighborhood metrics with a general framework which orders pixels based on a sequence of sorting functions which uses both global and local information to remap the image greylevels. We tested a novel sorting key with the suggestion of using the original image greylevel as the primary key and a novel neighborhood distinction metric as the secondary key, and compared HE using proposed distinction metric and other HE methods such as global histogram equalization (GHE), HE using voting metric and HE using contrast difference metric. We found that our method can preserve advantages of other metrics, while reducing drawbacks of them and avoiding undesirable over-enhancement that can occur with local histogram equalization (LHE) and other methods.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.12
• /
• pp.1603-1613
• /
• 1995

The goal of enhancement is to improve the perceptual aspect and visual appearance of images for human viewers. The objectives of image enhancement vary according to its specific application and an image enhancement algorithms used for a specific objective may not be accepted in some other applications. In this paper we review some of conventional enhancement techniques, such as global histogram equalization(GHE), local histogram equalization(LHE), clipped histogram equalization(CHE). We also describe some modified version of these algorithms. The proposed method is to detect detail information. We distinquish edge from nonedge and apply histigram equalization respectively. Simulation results demonstrate the performance of the proposed method for medical image.