Lab Image and Field Image Contrast Quality Differentiation

Image processing performance can be improved with the process of resizing the original input image to one standard size. Most of the previous studies used a standard size of 256 x 256 to provide the image as the image pre-processing material. The result of different image size dimension are shows in...

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Veröffentlicht in:International journal of innovative technology and exploring engineering 2020-01, Vol.9 (3), p.3428-3431
Hauptverfasser: Albahari, Elmaliana, Madzin, Hizmawati, Rahmat, Rahmita Wirza O.K., Mustaffa, Mas Rina, Mohd Noor, Mohamad Roff
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container_title International journal of innovative technology and exploring engineering
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creator Albahari, Elmaliana
Madzin, Hizmawati
Rahmat, Rahmita Wirza O.K.
Mustaffa, Mas Rina
Mohd Noor, Mohamad Roff
description Image processing performance can be improved with the process of resizing the original input image to one standard size. Most of the previous studies used a standard size of 256 x 256 to provide the image as the image pre-processing material. The result of different image size dimension are shows in this research to proven that image resizing is important. Reducing image dimension size can help to improve system performance. At the same time, it is importance to keep the image quality. This study shows that by reducing image dimension, it can improve the computer or system performance more than 95%. Image quality can be measured to get helpful information for the study after resizing the image into the same standard size. In this study, measurement of contrast levels was taken to compare the quality differences between image labs and field images. It turns out that the quality of lab image produces high-quality images with good brightness over image field image.The best quality image is the images that have low contrast. Therefore in this research paper we used CLAHE method to enhance the contrast and brightness for field image.
doi_str_mv 10.35940/ijitee.C9240.019320
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title Lab Image and Field Image Contrast Quality Differentiation
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