Enhancement of low quality thick blood smear microscopic images of malaria patients using contrast and edge corrections

Malaria becomes one of the diseases that cause many deaths in Indonesia, particularly in Eastern Indonesia. Parasite readings in many fields of thick blood smear microscopic images become the gold standard for the diagnosis of malaria. Therefore, it requires high-quality smear image that easily readable existence of parasites. Lack of health infrastructure, especially microscopy specifications, in endemic areas affect the availability of such smear images. Images that produced under these conditions have low quality that have characteristics: blurred, the diminished true color of object, unclear boundary, and the low contrast between the object and the background. Therefore, in this study, we propose image enhancement technique to improve the readability of parasite in the low quality of thick blood smear image. The proposed method consists of two parts, namely contrast and edge corrections. Contrast correction utilizing the integration of contrast correction globally and locally respectively using Dark Stretching and Contrast Limited Adaptive Histogram Equalization (CLAHE). Meanwhile, edge correction utilizing Unsharp Masking Filtering (UMF) to improve the edge of objects in an image. The results show that the proposed method is better in the image entropy than other methods. While the value of MSE and PSNR better if range of the histogram image is short. This value means that the proposed method can produce images that contain more information than the other methods and have a good effectiveness. So the proposed method successfully improve readability parasite in the low quality of thick blood smear image.