ADAPTIVE CONTRAST ENHANCEMENT USING OPTIMAL EQUALIZATION OF 2-DIMENSIONAL HISTOGRAM

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IRAVANI SAHAR; EZOJI MEHDI

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Journal: MACHINE VISION AND IMAGE PROCESSING Year:2016 | Volume:2 | Issue:2 Page(s): 15-24

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Information Journal Paper

Title

ADAPTIVE CONTRAST ENHANCEMENT USING OPTIMAL EQUALIZATION OF 2-DIMENSIONAL HISTOGRAM

Author(s)

IRAVANI SAHAR | EZOJI MEHDI | Issue Writer Certificate

Keywords

CONTRAST ENHANCEMENT

DIMENSIONAL HISTOGRAM

HISTOGRAM EQUALIZATION

Abstract

In this paper, an adaptive image CONTRAST ENHANCEMENT algorithm based on an optimization problem in two DIMENSIONAL HISTOGRAM domain is presented. To reduce the unwanted effects of the histogram adjustment, through this optimization-similar to the other methods- the 2D histogram of enhanced image is found in close proximity to input image histogram and uniform distribution, simultaneously. In addition, different from the other methods, by adaptive adjusting the components of a weight matrix, local information is counted. Experimental results in the quantitative and qualitative assessments on a wide range of images demonstrate the performance of the proposed method. Tests have shown that with the addition of the adaptive adjusting the weights, the average performance in CONTRAST ENHANCEMENT increases 75 and 3 percent from the viewpoint of the AMBE_N and DE_N, respectively.

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APA: Copy

IRAVANI, SAHAR, & EZOJI, MEHDI. (2016). ADAPTIVE CONTRAST ENHANCEMENT USING OPTIMAL EQUALIZATION OF 2-DIMENSIONAL HISTOGRAM. MACHINE VISION AND IMAGE PROCESSING, 2(2 ), 15-24. SID. https://sid.ir/paper/265707/en

Vancouver: Copy

IRAVANI SAHAR, EZOJI MEHDI. ADAPTIVE CONTRAST ENHANCEMENT USING OPTIMAL EQUALIZATION OF 2-DIMENSIONAL HISTOGRAM. MACHINE VISION AND IMAGE PROCESSING[Internet]. 2016;2(2 ):15-24. Available from: https://sid.ir/paper/265707/en

IEEE: Copy

SAHAR IRAVANI, and MEHDI EZOJI, “ADAPTIVE CONTRAST ENHANCEMENT USING OPTIMAL EQUALIZATION OF 2-DIMENSIONAL HISTOGRAM,” MACHINE VISION AND IMAGE PROCESSING, vol. 2, no. 2 , pp. 15–24, 2016, [Online]. Available: https://sid.ir/paper/265707/en

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