Real-Time Processing of Contrast Limited Adaptive Histogram Equalization on FPGA

Kokufuta, Kentaro; Matsumoto, Tsutomu

doi:10.1109/fpl.2010.37

Cited by 28 publications

(8 citation statements)

References 7 publications

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“…Paper [8,6] use adaptive threshold, which compute the threshold iteratively. Our method was inspired by these methods.…”

Section: Related Workmentioning

confidence: 99%

An Improved Enhancement Method for Infrared Images

Zhou¹,

Su²,

Yang³

et al. 2017

dtcse

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Abstract. Infrared images play important roles in the national defense and civil applications. The enhancement of the infrared images aims to improve the visual quality of images so that the result is more suitable for specific applications or an observer. In this paper, we explored the histogram equalization method which is a common technique for image enhancement, and proposed an improved enhancement method for infrared images. More specifically, we proposed a method to automatically select the threshold for histogram segmentation by an iterative method, and process the pixel brightness locally by considering the visual factor. We tested our method on different types of infrared images, and quantitatively compare our method with previous methods. The results show that out method improved visual quality of the images and also provide higher entropy and peak signal noise ratio.

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“…Paper [8,6] use adaptive threshold, which compute the threshold iteratively. Our method was inspired by these methods.…”

Section: Related Workmentioning

confidence: 99%

An Improved Enhancement Method for Infrared Images

Zhou¹,

Su²,

Yang³

et al. 2017

dtcse

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“…Through the improvement of intensity values in each region, AHE improves the visibility of local details in an image [13]. The images are subdivided into regions called as 'tiles' which are user-defined square subsections of the original image.…”

Section: Clahementioning

confidence: 99%

Color image enhancement techniques in Wireless Capsule Endoscopy

Vani¹,

Prashanth²

2015

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-Tact-15)

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Wireless Capsule Endoscopy (WCE) is available since 2001 and has been established as one of the principal approaches to examine the entire GI tract particularly the small bowel. WCE images are dark and difficult to visualize for diagnosis by physicians. Image enhancement methods to improvise the contrast of the images maybe adopted. The experimental results of various image enhancement techniques such as histogram equalization, Multi Scale Retinex and Contrast limited Adaptive Histogram Equalization techniques were being compared and analysed. Image enhancements techniques were applied for both on color image and gray scale image. The experiment results suggests that CLAHE provides better contrast improvement of WCE images, while Multi Scale Retinex provides better human visualization. The proposed future work is in progress in image fusion process; adapting both CLAHE and MSRCR image enhancement techniques.

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“…For LHE need to do GHE in a distinct region for every pixel in the image, it is very computationally intensive and not acceptable for most applications. Some implement have been realized for real-time computation of LHE using an FPGA [4] [5]. However, Simplifications are applied to the algorithm which would degrade the performance.…”

Section: Introductionmentioning

confidence: 99%

A novel contrast enhancement algorithm in IR imaging systems

Chen

Yu²,

Yu-jue³

et al. 2011

2011 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology

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The contrast enhancement of infrared image is useful and important to the infrared image system. The current techniques of local enhancing exists either over-enhancing or high complexity problems. In this paper, we propose a novel contrast enhancement algorithm which combines histogram equalization based methods (HEBM) and an improved unsharp masking based methods (UMBM). This proposed algorithm uses HEBM to achieve global contrast enhancement and UMBM to achieve local contrast enhancement. Some elaborate strategies are applied to the algorithm to avoid the overenhancement and magnification of noise when contrast is enhanced. The article is organized as follows. First, we review the techniques developed in the literature for contrast enhancement. After then, we introduce the new algorithm in details. The performance of the proposed method is studied on experimental IR data and compared with those yielded by two well established algorithms. The developed algorithm has good performance in global contrast and local contrast enhancement with noise and artifact suppression.

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Real-Time Processing of Contrast Limited Adaptive Histogram Equalization on FPGA

Cited by 28 publications

References 7 publications

An Improved Enhancement Method for Infrared Images

An Improved Enhancement Method for Infrared Images

Color image enhancement techniques in Wireless Capsule Endoscopy

A novel contrast enhancement algorithm in IR imaging systems

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