Optimization Contrast Enhancement and Noise Reduction for Semantic Segmentation of Oil Palm Aerial Imagery

Contrast improvement and noise reduction are needed to improve aerial images prone to interference during data collection. Contrast limited adaptive histogram equalization (CLAHE) is a histogram equalization (HE) development method that is commonly used for contrast improvement. Median blur (MB) is one of the methods used for noise reduction. Combining these two techniques helps optimize the preprocessing process before semantic segmentation analysis is carried out in image maps. The results of testing experiments with U-Net VGG-16 and VGG-19 on image maps show a detailed representation of the predicted pixel class. Comparing accuracy with state-of-theart methods shows that contrast enhancement and noise reduction are better than the previous method. The highest average result for combining CLAHE+MB with U-Net VGG-16 was 76.5 and VGG-19 was 73.8, and the highest accuracy for image sample testing was 87.94 with U-net VGG-16.