Abstract
Improved image is a process on the image that initially has a quality that is less good or has noise. In this image improvement operation image quality will be improved so that the image produces better quality. Image improvement methods used are contrast stretching, histogram equalization, low pass filter and Gaussian filtering. In this study compare contrast stretching method, histogram equalization, low pass filter and Gaussian filtering to improve image quality. Performance of each method would be calculated by finding the value of Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). This study compares contrast stretching methods, histogram equalization, low pass filter and Gaussian filtering to improve image quality. Total data of malaria parasite image is 120. The data consist of image of malaria parasite falciparum, vivax, malariae along with stage that is ring, tropozoit, skizon and gametocyte. Evaluate the performance of each method by finding Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) values. The result is a contrast stretching provides better image quality against malaria parasite image.
Highlights
The image of malaria parasite comes from Health Laboratory Center of North Sumatera Province
There are four image repair methods used for comparisons such as contrast stretching, histogram equalization, low pass filter and Gaussian filtering
The result of image improvement method cannot be distinguished because it looks the same between contrast stretching method, histogram equalization, low pass filter and Gaussian filtering. It measured the performance of MSE (Mean Square Error) and PSNR (Peak Signal to Noise Ratio) image
Summary
The image of malaria parasite comes from Health Laboratory Center of North Sumatera Province. There are four image repair methods used for comparisons such as contrast stretching, histogram equalization, low pass filter and Gaussian filtering. Previous studies had not compared the four methods of image repair using contrast stretching, histogram equalization, low pass filter and Gaussian filtering to identify three types of malaria disease consisting of malaria, falciparum and vivax with ring stage, trophozoite, skizon and gametocyte. The result of image improvement method cannot be distinguished because it looks the same between contrast stretching method, histogram equalization, low pass filter and Gaussian filtering. It measured the performance of MSE (Mean Square Error) and PSNR (Peak Signal to Noise Ratio) image. The best image repair method will be used in the stage of the region of interest (ROI) and used to identify the type of malaria and its stadium
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