Image enhancement using the image sharpening, contrast enhancement, and Standard Median Filter (Noise Removal) with pixelbased and human visual system-based measurements

Erwin, Erwin (2017) Image enhancement using the image sharpening, contrast enhancement, and Standard Median Filter (Noise Removal) with pixelbased and human visual system-based measurements. In: 2017 International Conference on Electrical Engineering and Computer Science (ICECOS), 22-23 Aug. 2017, Palembang.

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Abstract

In this paper, we explained the three methods of image enhancement: Image Sharpening by sharpening the edges, Contrast Enhancement using Standard Histogram Equalization and Standard Median Filtering where noise is filtered using these methods first and finally noise is eliminated. Then we put on the measurement parameters using a calculation based on the image quality of the pixel MSE and PSNR and calculations based on human vision system (HVS) that SSIM. The dataset we use is BSDS300 Berkeley and the environment is Matlab 2016a. We can state that the image quality measurement is good where the results are accurate so that we can determine the best methods too. We got SSIM value is close to 1 and the value obtained MSE and PSNR is minimum in Image Sharpening which is mean Image Sharpening is best of basic methods in Image Enhancement.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Dr Erwin Erwin
Date Deposited:	20 Apr 2020 01:05
Last Modified:	20 Apr 2020 01:05
URI:	http://repository.unsri.ac.id/id/eprint/29088

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Image enhancement using the image sharpening, contrast enhancement, and Standard Median Filter (Noise Removal) with pixelbased and human visual system-based measurements. (deposited 20 Apr 2020 01:05) [Currently Displayed]
- Image enhancement using the image sharpening, contrast enhancement, and Standard Median Filter (Noise Removal) with pixelbased and human visual system-based measurements. (deposited 12 Oct 2020 00:42)

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